A Project Report on Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TE

Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore Sl.no

Topic

Page No

1.

COMPANY PROFILE • An introduction • Profile

2.

BUSINESS INTELLIGENCE AND IT’S USE 7.

IN DECISION MAKING •

1.

Definition

• Evolution Of Business Intelligence:

3.

MARKET

ANALYSIS OF BUSINESS INTELLIGENCE SOFTWARE Market Growth For Business Intelligence Registered strong holds in Business Intelligence Market Share Trend Of The Companies Comparative Analysis

11.

4.

INDUSTRIAL USE OF BUSINESS INTELLIGENCE

14.

5.

TOOLS USED INTELLIGENCE

18.

• • • •

IN

BUSINESS

6.

7.

8.

UNDERSTANDING BUSINESS INTELLIGENCE USING MICROSTRATEGY 7i

30.

FUTURE OF BUSINESS INTELLIGENCE

66.

ANNEXURES

72.

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore

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Business Intelligence And It’s Use In Decision Making� At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore

Business Intelligence Definition: A term which represents those systems that help companies understand what makes the wheels of the corporation turn and to help predict the future impact of current decisions.

These systems place a key role in strategic planning process of the corporation. Systems that exemplify business intelligence include medical research, customer profiling, market basket analysis, customer contact analysis, market segmentation, scoring, product profitability, and inventory movement Business Intelligence provides business roadmaps to deliver solutions for business analysis, which includes data models, meta-data and analytical applications. By having these roadmaps, we deliver superior business value through improved return on investment, time value by enabling fast solution delivery, and technical value through open database.

Information is typically obtained about customer needs, customer decision making processes, the competition, conditions in the industry, and general economic, technological, and cultural trends.

Business intelligence is carried out to gain sustainable competitive advantage, and is a valuable core competence in some instances.

Business Intelligence (BI) is a code-name for a range of technologies which unlock knowledge that is hidden in business data and tell us how to use it more effectively. The overall objectives of BI are to improve planning, productivity, service quality, and profitability by making information and data more comprehensible and using business knowledge more effectively. Business Intelligence helps us to use business data for competitive advantage .

Business Intelligence allows management to gain insight into their business by analyzing business data to spot trends or using "what-if" analysis for scenario forecasting. BI technologies provide management with up-to-date information on vital business aspects of their operations.

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Business Intelligence And It’s Use In Decision Making� At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore

Evolution Of Business Intelligence: Ever since mainframe computers began accumulating vast storehouses of data in the early 1960s, managers and executives have sought ways to turn random facts and figures into useful information upon which to base sound business decisions.

But it wasn't until the arrival of relational databases and client/server technology in the early 1990s that companies took advantage of the market's need for decision support systems to create and define a new industry, which is now widely known as business intelligence (BI). Business intelligence allows organizations to extract useful, actionable information from a rapidly growing inventory of disparate data sources, including multiple database platforms, packaged applications, data warehouses, data marts and e-business systems .

The major database application vendors typically supply basic querying and reporting functionality for their own products. BI vendors provide tools that can be used across the organization to access, analyze and share information from a variety of sources -- a giant step in the right direction for business decision-makers needing the big picture.

As the use of BI has matured, there has been increased interest in analytic applications, a logical extension of the business intelligence concept. Analytic applications provide users with prepackaged solutions to common business problems such as customer, sales and campaign analysis. Although analytic applications have been available in areas such as financial budgeting for many years, they typically relied on older, proprietary systems and covered only a small fraction of the overall needs of the enterprise. Over the last few years, analytic applications have gained popularity in new areas, particularly for the analysis of e-business and click stream information.

Analytic applications provide key additional BI benefits to specific groups of end users through the use of "best practice" analysis techniques -- in particular business areas and "closed loop" integration with operational systems. However, their implementation has not always been painless. While they address a business need for a particular population, they perpetuate the problem of stovepipe information sources and may make it more difficult than ever to get an overall view of the enterprise. As Gartner noted in a May 2001 report: "Packaged BI applications

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore may seem appealing in the context of a particular application, but organizations should ensure that they will support BI in a broader context as a strategic initiative."

Hence the notion of "enterprise analytic applications" which provide a common platform for analytic applications throughout the organization. The situation is similar to the changes that have taken place in the packaged operational applications market, where companies first implemented packaged solutions rather than creating them from scratch (People Soft for human resources, for example) then quickly demanded integrated systems that tied together operations across the organization, pioneered by companies such as SAP and rapidly followed by the other vendors.

The chief business benefits of an enterprise analytic applications approach are: •

A single version of the truth across an entire enterprise.

•

Predefined best practice analysis techniques in a variety of different business areas.

•

A consistent BI strategy that leverages existing resources.

With these constants in mind, let's examine the evolutionary path of enterprise analytic applications, including where they are today, where they're going and how to create a BI strategy that works.

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore

MARKET ANALYSIS OF BUSINESS INTELLIGENCE SOFTWARE

I. Market Growth For Business Intelligence: The BI market has experienced modest growth in recent years (5%-10% annually). We expect this level of growth to increase somewhat, to 10%-15%, in 2004.

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore

II. Registered strong holds in Business Intelligence Actuate

Business Objects

Cognos

Computer Associates

Hummingbird

Hyperion

Information Builders

Microsoft

MicroStrategy

Oracle

PeopleSoft

ProClarity

SAP

SAS

Siebel

III. Market Share Trend Of The Companies :

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore

IV. Comparative Analysis: 2003

Vendor

(preliminary figures) Market Share position (%)

Microsoft Hyperion Solutions (incl Brio) Cognos (incl Adaytum) Business Objects (incl Crystal) MicroStrategy SAP Oracle Cartesis Applix MIS AG Geac SAS Institute

1 2 3 4 5 6 7 8 9 10 11 12

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26.1% 21.9% 14.2% 7.7% 6.2% 5.8% 4.0% 3.1% 3.0% 3.0% 2.0% 0.9%

2002

2001

2000

Market Share Market Share Market Share position (%) position (%) position (%) 1

24.4%

2

21.1%

3

11.5%

2

23.3%

1

24.0%

1

27.4%

3

14.7%

3

13.7%

2

13.5%

4

7.4%

4

7.6%

6

7.4%

5

5.4%

6

6.8%

5

9.1%

6

5.2%

7

5.4%

8

2.9%

7

4.7%

5

7.0%

4

9.9%

9

2.6%

9

2.4%

11

2.2%

8

2.6%

8

2.5%

7

3.0%

12

2.1%

11

2.1%

12

2.1%

10

2.2%

10

2.3%

10

2.5%

13

1.1%

13

1.2%

13

1.6%

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore

INDUSTRIAL USE OF BUSINESS INTELLIGENCE

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore I. Why should Industries use business intelligence?

Business intelligence enables the industry achieve the following: Companies achieve returns from business intelligence solutions in three main areas: •

More efficient reporting. Without business intelligence, many companies often have teams of employees spending time to gather, aggregate, and analyze information from different systems to provide reports to management. Business intelligence can significantly reduce the amount of time spent developing reports on different aspects of the business. What’s the return? Companies can reduce employee time spend developing reports and reduce finance staff headcount or redeploys finance staff to other activities.

•

Improved information for decision-making. Because companies can access, view, and analyze numbers that were either too unwieldy, distributed, or expensive to access, managers can get the reports they need to make effective decisions and correct problems.

What’s the return? Companies could used improved reporting information to identify where they were missing revenue generation opportunities, to reduce overhead costs based on utilization, and to manage billing and accounts receivables. For example, one shipping company used business intelligence to analyze shipping information and determine where it should be charging customers more – and where it could reduce internal costs.

•

Improved customer management. Companies can use business intelligence to identify customer and market trends and use that information for forecasting, planning, marketing, and promotions. In cases where a customer is part of a supply chain, companies can also open access to business intelligence information directly to the customer to reduce management costs and streamline interaction. Where’s the return? Nucleus found companies could reduce customer support costs by providing customers with self-service access to information, or increase profits based on better customer data. For example, one bank increased its collection rate by using business intelligence to identify delinquent borrowers.

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore II. A few tangible benefits that can be listed are: •

Build profits by targeting profitable activities.

•

Increase customer loyalty and retain customers for life.

•

Increase the accuracy and timeliness of sales forecasts.

•

Achieve budgeted sales.

•

Increase the proportion of high-value customers in your customer mix.

•

Reduce low-yield activities in the sales process.

•

Deploy higher-yield promotions and advertising.

•

Predict future behavior of prospects and customers.

•

A way to access data in a common format from multiple sources

•

A way to measure business goals by analyzing cross-departmental data

•

See who the good, bad and ugly customers are at a glance

•

Track customer behavior to improve service and relationships

•

Track specific product sales across regions and distributors to improve production and supply

•

Track internal business trends to improve processes

•

Track external market trends to improve competitiveness

•

Fine tune pricing and marketing policies

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore

TOOLS USED IN BUSINESS INTELLIGENCE

Tools used in BI: People doing business intelligence have developed tools that ease the work, especially when the intelligence task involves gathering and analyzing large amounts of data. These are some tools commonly used for business intelligence: •

Data warehouses

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Business Intelligence And It’s Use In Decision Making� At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore A data warehouse comprises a computing system used to store information regarding an organization's activities in a database. The database design favors reporting on and analyzing the data in order to gain strategic information and to facilitate decision-making.

Data warehouses may hold large amounts of information, sometimes in smaller logical units called Data marts. Often the schemas of data marts are stored in what are known as "Star Schemas", or Dimensional Modeling form; however there is no industry standard requiring that the schemas of data marts be in any particular form. There is, in fact, some controversy about the most useful form of data mart schemas.

Conventional database systems use highly normalized data formats to ensure consistency of data and minimal use of space. However this often means that transactions and queries against a fully normalized database perform slowly. Data warehouses often use a more de-normalized (relaxed) format. This speeds up queries, and has the additional benefit that the schema will be more intuitive to non-administrative users as they are exploring it. For example, rather than having a single record in a table contains customer information, that information may be replicated across a whole series of tables.

OLAP (online analytical processing) tools are generally designed to work with de-normalized databases although there are tools that work with special data warehouse schemas stored in third normal form (normalized).

Data warehouses are usually accessed (queried) via "data marts", which are purpose-specific access points to or sub-sets of the warehouse. Data marts are designed to answer the probable queries of a given kind of user.

Normally a data warehouse does not store current information on an individual business activity.

It is often used for collective processing for all business units across a corporation.

Computing in data warehouses is often referred to as Online Analytical Processing (OLAP), in contrast to Online Transaction Processing (OLTP) -- used for normal business activities. Data from Enterprise resource planning (ERP) systems and other related business software systems is imported into data warehouses periodically for further processing.

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Business Intelligence And It’s Use In Decision Making� At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore •

Data mining

Data mining is the practice of automatically searching large stores of data for patterns. To do this, data mining uses computational techniques from Statistics and Pattern recognition.

Data mining has been defined as "The nontrivial extraction of implicit, previously unknown, and potentially useful information from data" [1] and "The science of extracting useful information from large data sets or databases" [2]. Although it is usually used in relation to analysis of data, data mining, like artificial intelligence, is an umbrella term and is used with varied meaning in a wide range of contexts.

It is also known as knowledge-discovery in databases (KDD).

Used in the technical context of data warehousing and analysis data mining is neutral. However, it sometimes has a more pejorative usage that implies imposing patterns (and particularly causal relationships) on data where none exist. This imposition of irrelevant, misleading or trivial attribute correlation is more properly criticized as "data dredging" in the statistical literature.

Used in this latter sense, data dredging implies scanning the data for any relationships, and then when one is found coming up with an interesting explanation. (This is also referred to as "over fitting the model".) The problem is that large data sets invariably happen to have some exciting relationships peculiar to that data. Therefore any conclusions reached are likely to be highly suspected. In spite of this, some exploratory data work is always required in any applied statistical analysis to get a feel for the data, so sometimes the line between good statistical practice and data dredging is less than clear.

A more significant danger is finding correlations that do not really exist. Investment analysts appear to be particularly vulnerable to this.

Most data mining efforts are focused on developing a finely grained, highly detailed model of some large data set. In Data Mining For Very Busy People [3], researchers at West Virginia University and the University of British Columbia discuss an alternate method that involves finding the minimal differences between elements in a data set, with the goal of developing simpler models that represent relevant data.

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore There are also privacy concerns associated with data mining. For example, if an employer has access to medical records, they may screen out people with diabetes or have had a heart attack.

Screening out such employees will cut costs for insurance, but it creates ethical and legal problems.

Data mining government or commercial data sets for national security or law enforcement purposes has also raised privacy concerns. [4] There are many legitimate uses of data mining. For example, a database of prescription drugs taken by a group of people could be used to find combinations of drugs with an adverse reactions.

Since the combination may occur in only 1 out of 1000 people, a single case may not be apparent.

A project involving pharmacies could reduce the number of drug reactions and potentially save lives. Unfortunately, there is also a huge potential for abuse of such a database.

Basically, data mining gives information that wouldn't be available otherwise. It must be properly interpreted to be useful. When the data collected involves individual people, there are many questions concerning privacy, legality, and ethics.

•

Predictive Modeling

Predictive Modeling techniques are used to build models that predict or forecast numerical outcomes such as sales volume.

• Genetic Algorithms Genetic Algorithms an advanced algorithmic method can be used to solve complex optimization problems such as scheduling and logistics.

• Decision Support System: Decision Support System provides the decision maker with models and data to support decisionmaking tasks. These systems can either contain expert knowledge, which has been captured, or rules and models developed from data. These systems support delegation of decision-making authority by distributing knowledge and allow effective decision-making in very complex situations.

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore • Intranet Web Intranet Web technologies make business information available company-wide in a format that addresses employees’ needs.

Sectors in which BI can be used: I. Communication: Business intelligence solutions can be used in communications industry to increase revenue, reduce operational costs, and increase customer retention. Leading wire line, wireless, broadband, ISP, and satellite carriers around the world are using BI solution of choice, and in many cases, as the enterprise standard. BI enables them to: 

Identify and segment customers to enable effective retention and cross-sell strategies



Integrate management, operational and financial reporting to improve performance



Improve revenue assurance across the organization



Reduce and control operational costs through optimized performance of all resources



Effectively service customers throughout the multi channel network

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore 

Differentiate themselves by delivering on service level agreements and service quality

II. Customer products: Business intelligence solutions improve performance in the consumer product goods (CPG) industry. Our CPG companies include apparel makers; makers of personal and household care products; food and beverage manufacturers; paper and business forms makers; and pet products companies. Business intelligence solutions enable CPG companies to: •

Determine profitable trading partners and enable collaborative process improvement

•

Integrate management and financial reporting to improve performance

•

Reduce and control sales and marketing costs through improved analysis

•

Manage assets and improve capital utilization through accurate forecasting and analysis

•

Efficiently service customers over the internet

III. Energy: Energy companies that succeed will be those that can expand into non-traditional markets by shaping their products and services to new and existing customers.

Business intelligence solutions have helped many energy companies to redefine their business.

By carrying out trend analysis and tracking the day-to-day operations across all parts of the business, companies can react immediately to market opportunities or threats.

Business intelligence solutions help energy companies in many ways, by enabling them to: 

Optimize the supply chain by providing data access to suppliers, distributors, and customers to enhance performance and responsiveness (all while reducing costs)



Improve stock control by providing visibility across the organization and supply chain to enhance just-in-time management and reduce excess inventory

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore 

Minimize procurement inefficiencies by analyzing supplier performance, and driving negotiations and pricing structures



Respond quickly to market opportunities by tracking and analyzing operational data from inventory, financial, point-of-sale, and marketing



Differentiate and refine product offering by analyzing historical information and assessing product profitability on a geographic basis



Strengthen customer relationships and increase their value by tracking customer behavior and service issues, better targeting promotions, and improving service delivery

IV. Financial Services: Business intelligence solutions improve performance in the banking, brokerage, consumer credit, investment banking and insurance industries. With our analytical and reporting solutions, financial services companies can: 

Identify profitable customers and retain them



Improve management of financial performance



Automate compliance with reporting standards and regulations



Efficiently service customers and agents over the internet

V. Government And Public Sector: Government, public sector, educational and non-profit organizations use BI to track, manage, understand, and improve mission performance.

Business intelligence solutions enable these organizations to: 

Integrate mission effectiveness and financial performance through enterprise performance management



Reduce and control operational costs through improved sourcing, supply chain, and logistics management

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore 

Implement e-Government initiatives to effectively deliver services over the internet



Identify and segment constituents to enable optimal service delivery



Align human capital with agency and mission requirements

VI. Health Care: Escalating costs, increased government legislation, and a rapidly aging population, have all created a significant strain on today's healthcare industry. The challenge is to provide higher quality customer care while keeping costs to a minimum.

Many leading healthcare organizations are using our business intelligence solutions as a vital weapon in understanding and managing their critical performance indicators.

Information access and analysis that goes company-wide has numerous benefits. It enables healthcare businesses to monitor successful treatments and optimize the results for effective clinical decisions. Accurate information also helps companies to identify efficient service and workflow practices.

Business intelligence solutions help healthcare companies, by enabling them to: 

Increase workflow efficiencies by analyzing consolidated data from clinical, administrative, and financial areas



Improve patient care and optimize resource management by tracking and predicting healthcare service utilization



Meet government legislative controls by delivering measured and accountable patientcentric care metrics



Monitor and analyze patient diagnosis and condition to facilitate timely and effective clinical decisions



Control costs, improve contracting decisions, and eliminate waste by closely managing inventory and provider performances



Increase efficiency and detect fraud by analyzing historical information, and tracking and closely monitoring current claims data

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore VIII. Manufacturing: The goal of today's manufacturing companies is to be recognized as performing "world-class manufacturing" organizations. This status demands an agile enterprise that is always one step ahead of the competition.

To ensure competitive advantage, manufacturing companies need to cultivate a responsive environment and deliver major improvements in lead time, product quality, and lower production costs.

Business intelligence solutions help manufacturing companies in many ways, by enabling them to: 

Improve customer relationships and increase their value by closely tracking purchasing behavior, anticipating demand, and responding faster to changing requirements



Respond quickly to changing markets and company sensitivities by integrating, analyzing, and tracking data from disparate sources



Accelerate new product time-to-market by integrating decision processes across engineering design, manufacturing, and marketing departments



Reduce inventory investment by providing inventory visibility across the supply chain to enhance just-in-time management



Improve planning and scheduling by analyzing forecasts, orders, lead times, utilization throughput, and fill rate, to quickly identify opportunities or threats



Maintain and develop quality assurance by analyzing product history, to continuously update and improve quality objectives and get closer to market



Improve the procurement cycle by analyzing and tracking supplier performance on critical measures such as order fulfillment time, quality, and accuracy



Intelligently select and apply world-class techniques by analyzing internal and external data to understand optimal techniques for individual organizations

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore

IX. Pharmaceuticals: With improved access to information via the Internet, increased personal wealth, and longer life expectancy, consumers today have a greater say in their medical treatment.

These socio-economic factors are driving a demand for groundbreaking new products and they are dramatically impacting the business dynamics of the global pharmaceutical industry.

Strong growth also brings new challenges. Pharmaceutical companies are under increased pressure to be first to market, which requires a dramatic reduction in drug development cycles. At the same time they must contain and reduce operational costs, and comply with increasingly stringent regulatory controls.

Business Objects BI solutions enable our customers to support faster and more cost-effective innovation, work more efficiently with collaborative partners, and produce and deliver products more effectively.

BI solutions help pharmaceuticals companies in many ways, by enabling them to: 

Identify the products that yield the most appropriate results with a clinical trial research process that segments, tracks, analyzes, and shares test results



Maximize the supply chain by sharing production information with suppliers, tracking product quality, optimizing stock replenishment, and monitoring vendor performance



Optimize campaign creation and implementation by analyzing the effectiveness of marketing strategies



Increase sales productivity by understanding sales activities, sales territory, and representative performances, and by providing customized data access to ensure that customer relationship management goals are met and exceeded

X. Retail:

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore Business intelligence solutions improve performance in the retail sector. Retail Sector include department stores; discount and outlet stores; supermarkets and convenience stores; consumer electronics and home furnishings retailers; and catalog and mail order companies. Business intelligence solutions enable retailers to: 

Improve purchasing, forecasting, and distribution management



Optimize product profitability and increase effectiveness of marketing campaigns



Identify and segment customers to enable retention strategies



Integrate management and financial reporting to improve performance



Reduce and control operational costs through optimized store performance



Effectively service customers throughout the multi channel network

Case Study I: Using the Web to distribute business intelligence is the approach Pfizer Inc. is taking, says Lawrence Bell, senior manager of the New York-based company's U.S. pharmaceutical information architecture team. Pfizer's global, distributed operation simply couldn't work out of one monolithic warehouse that had to distribute information about regional sales trends to sales and marketing professionals.

To deal with those challenges, Pfizer began using Informix Corp.'s ETL tool, Ardent Datastage, to create a distributed database running on hubs around the world that could be updated quickly and accurately on demand.

Pfizer uses a Datastage utility to allow replication on the fly using the Internet's file transfer protocol so the system can support frequent updates. The system is used to deliver volumes of data that Pfizer "feeds downstream" to marketing and sales divisions worldwide to help them evaluate product sales and trends.

Along with the standard business data sources, BI applications also let firms add nontraditional data sources.

Case Study II: Babasabpatilfreepptmba.com

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Business Intelligence And It’s Use In Decision Making� At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore The Dallas Teachers Credit Union (DTCU), used geographical data analysis - which draws information about the physical location of bank customers or prospective customers - to increase its customer base from 250,000 professional educators to 3.5 million potential customers virtually overnight The increase gave the credit union the ability to compete with larger banks that had a strong presence in Dallas.

"We're now competitive with Wells Fargo and [Bank of America]," says DTCU Senior Vice President and CIO Jerry Thompson. "We're even, if not ahead, of the big guys." The sudden access to a whole new market came from geographical data the DTCU used to find ways to improve its position.

The DTCU needed to increase its customer base to remain competitive. Changing its status from a profession-based service to a community-based service would do the trick, but such a change would require approval from the Texas State Credit Union Commission.

The DTCU needed to whip up a business plan and proposal to present to the commission. And much of the data in that proposal would have to reflect the credit union's detailed knowledge of the community's banking habits.

As a first step toward gathering the information it needed for the proposal, the credit union replaced a financial system with BI applications running on IBM's DB2 Universal Database.

Then it bought supplementary data compiled by Acxiom Corp. in Little Rock, Ark., to correlate credit scores, lifestyle statistics and locations of residents in the credit union's area, the mix-match was done to come up with the data that enabled DTCU to build there business plan and proposal to present to the commission which was approved by the commission. The credit was given to the BI solution that enabled them get the relevant data

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore

UNDERSTANDING BUSINESS INTELLIGENCE USING MICROSTRATEGY 7i

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore

Understanding BI using MICROSTRATEGY 7i : During the formative period, companies actively discovered many new ways to use their data assets for decision support, operational reporting and process optimization. And during this era of invention, BI technology vendors reacted the way software vendors always react to new evolving markets – that is, by building niche software to implement each new pattern of application that companies invented. These patterns of applications resulted in software products centered exclusively on one Style of BI, as follows: 1. Enterprise Reporting – Report writers were used to generate highly formatted static reports destined for broad distribution to many people.

2. Cube Analysis – Cube-based BI tools were used to provide simple slice-and-dice analytical capabilities to business managers.

3. Ad Hoc Query and Analysis – Relational OLAP tools were used to allow power users to query the database for any answer, slice-and-dice the entire database and surf down to the lowest level of transactional information.

4. Statistical Analysis and Data Mining – Statistical and data mining tools were used to perform predictive modeling or to discover the cause-and-effect correlation between two metrics.

5. Report Delivery and Alerting – Report Distribution engines were used to send full reports or alerts to large user populations based on subscriptions, schedules or threshold events in the databases.

At this point in time, most leading enterprises have purchased many different BI tool sets from many different vendors – with each tool targeted at a new BI application and each tool delivering user functionality focused on only one of the Styles of BI.

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Business Intelligence And It’s Use In Decision Making� At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore One way to look at these different Styles of BI is to place them in a two-dimensional space (Fig. 1) where the vertical axes represents the sophistication and interactivity of the analytical processes and the horizontal axis represents scale, or the size of the user population. We can then locate each of the 5 Styles of BI in a region on the grid, as we see in the figure below.

The most sophisticated and interactive Styles of BI are used by relatively small groups of users consisting of information analysts and power users, for whom data and analysis are their primary jobs. Less interactive Styles of BI deliver basic data and results that are applicable to very large user populations ranging from senior executives all the way to staff personnel. Leading organizations have recognized the benefits of putting information into the hands of all their employees, regardless of job title or function. Only the MicroStrategy architecture can deliver all 5 Styles of BI functionality to each and every user within an enterprise, offering different functionality levels within the 5 Styles of BI tailored for each user.

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore

The 5 Styles of BI In An Enterprise Application Scenario It is generally accepted now that from the CEO to the support staff, every employee of leading organizations analyzes business data to some degree, in some fashion. Their analyses may be deliberate and exploratory, they may be triggered automatically by threshold conditions or they may even be so embedded in everyday systems that their existence as BI per se may not even be recognized. One thing is clear: successful organizations make maximum use of their data assets through BI technology.

In the following scenario, a typical set of analyses and responses are used to demonstrate the 5 Styles of BI in practice.

BI Style 1: Enterprise Reporting When an enterprise wishes to distribute standard operational reports or financial reports to all stakeholders in the organization, Enterprise Reporting is used. Since the 1950s, corporations have found clear returns on their investment in operational and financial reporting. Consequently, Enterprise Reporting is the most widespread Style of BI – ranging from its earliest adoption as mainframe green-and-white banded paper reports to today’s web-based reports.

Consider the following scenario. A store manager receives Store Performance reports generated weekly by the Report Distribution engine. After a review of one such weekly report on store sales, the store manager notices that sales for computer peripherals have dropped off significantly from previous weeks. She clicks on her report and immediately drills to another enterprise report, which shows her that the 3 best selling hard drives are surprisingly underperforming

BI Style 2: Cube Analysis Cube Analysis is the Style of BI ideal for basic analysis that can be anticipated in advance. The analysis of sales by region for certain time periods, and the analysis of sales by product and by salesperson, for instance, could be useful to store managers looking for some underlying details on performance. In our scenario, the store manager digs deeper into the issue by running one of several analysis cubes that have been pre-built for the store managers. Analysis cubes provide people with a simple and safe environment that lets novice BI users easily conduct first-order analyses to try to uncover root

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore causes. This particular store manager’s analysis cube allows her to compare her store’s sales results against the sales plan, against sales results at other stores like hers, and against previous years’ seasonal patterns.

After flipping through various views of the data in her analysis cube, several things become apparent. The first is that most stores seem to be experiencing this same sudden slowdown in sales. The second is that this trend will quickly prevent her from achieving her revenue goals for this product category. And third, this downturn is inconsistent with seasonal sales patterns from the last 2 years for this kind of product. She concludes that there is a serious problem here, and that it is a corporate problem not unique to her store. She forwards a link to this analysis cube to a buyer at HQ, so they can see exactly what she has seen and delve deeper into the problem.

BI Style 3: Ad Hoc Query and Analysis Ad Hoc Query and Analysis is the Style of BI that enables true investigative analysis of enterprise data, down to the transaction level of detail. The buyer at HQ accesses the analysis cube but cannot determine what is happening based solely on predefined comparisons within the cube. The buyer needs to probe many more areas of the database to determine what is going on, and uses Ad Hoc Query and Analysis techniques to accomplish this. In our scenario, the buyer runs a parameterized, or prompted, report that lets him create an ad hoc report simply by answering some initial questions. His prompt answers automatically generate a report of inventory data for North America for the previous 2 months for the specific SKUs in question. He sees that there has been a steady stream of shipments from the warehouses to the stores, but also that a stoppage in warehouse replenishment has caused a depletion of inventory in the warehouses. He concludes that the problem lies somewhere further back in the supply chain.

Next, he drills down from the inventory report to a shipping report that indicates all seaborne shipments from Taiwan have been delayed, affecting the SKUs in question, as well as some other SKUs. He determines that the other SKUs likewise will soon experience a shortfall in sales. He informs the VP of Sales and all store managers of the results of his analysis, and sends the reports to the marketing department to determine the significance of the shipment delays on the company’s revenue and profits for the quarter.

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BI Style 4: Statistics and Data Mining Statistics & Data Mining is the Style of BI used to uncover subtle relationships (e.g. price elasticity) and forecast projections (e.g. sales trends), using set theory techniques, statistical treatment and other advanced mathematical functions. In our scenario, an analyst in the marketing department builds a model of the product line’s revenue and gross margins for the quarter as a function of shipment times, pricing and demand. After estimating the financial impact of the delayed shipments, the analyst recommends raising the price on the remaining items in stock to help cover the lost margins. She also recommends some new promotional spending to substitute alternative hard drives through a combination of in-store marketing and advertising.

BI Style 5: Report Delivery & Alerting A Report Delivery and Alerting engine allows enterprises to distribute vast numbers of reports or messages on a proactive and centralized basis, as well as allowing users to self-subscribe to report distributions. Report distribution can be initiated on a scheduled basis, as well as on an eventtriggered basis, such as a metric’s value falling below a target threshold. In our scenario, a task force continuously monitors the progress of new sales programs by subscribing to a distribution service that continuously measures sales performance of relevant SKUs, their margin performance and the costs for the new promotions. The service also continuously monitors the inventory levels in the warehouses and alerts all stakeholders as soon as the shipment delays are over, signaling that pricing and promotion should return to normal. Together, the team is able to make intelligent decisions, respond quickly to changing events, and preserve the company’s exceptional level of performance.

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore

The Problem with Multiple BI Tools for Different Styles of BI There are five macro forces that are obsolescing the “strategy” of isolated departmental islands of BI and the use of disparate departmental BI tools.

Problem 1.

Enterprise BI Applications Need to Access More Data and Support More Users – Departmental BI Lacks User and Data Scalability. Most companies have captured the lowhanging ROI fruit with their current array of departmental BI applications. Based on the almost universal success of these applications, companies are now emboldened to take it to the next level. And that means delivering much richer reports and analysis, from much larger pools of data and delivered to many more users. Unfortunately, departmental BI tools today cannot scale to these new levels. The very nature of their underlying architecture prohibits them from analyzing terabytes of data and delivering to expanding user bases. Companies need an industrial-strength BI platform designed for scale to replace departmental BI tools designed solely for interface functionality.

MICROSTRATEGY Enterprise BI

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore Problem 2.

Inconsistent Versions of the Truth Are Propagating Through the Enterprise – Multiple Islands of BI Result In Multiple Inconsistent Metadata Repositories. Multiple independent islands of departmental BI applications work fine when the number of applications is small.

When there are few applications, there is little overlap in analytical or reporting domains; inconsistencies in data definitions, in metric usage and business model are not readily evident.

However when the number of BI applications achieves a certain critical mass within the enterprise, there is an inevitable overlap in analytical and reporting domains. It becomes inevitable that multiple reports from multiple independent BI applications present inconsistent information, preventing a consistent version of the truth. As the number of applications increases, these inconsistencies undermine the integrity of all the BI applications.

Problem 3.

Users Are Increasingly Dissatisfied About Being Forced to Use Multiple BI Tools – Multiple User Interfaces Are Problematic. When the number of BI applications is few, any given person only uses one of those applications, and hence only uses the one BI technology associated with that application. As the number of BI applications increases, more and more people will be accessing multiple BI applications, and hence using multiple different BI user interfaces to view reports and manipulate those reports. This means that BI users need to learn different ways to do everything, including such common actions as finding reports, running reports, scheduling reports, editing reports, saving reports, sharing reports, answering prompts, sorting the data and pivoting the data. With two different tools, users will face challenges. With three different tools, users will be reluctant or unable to use the multiple applications. With four or five different tools, this becomes a valid reason for user rebellion.

Problem 4.

IT Organizations Cannot Afford the Excessive Cost of Managing Multiple BI Technologies– Disparate BI Technologies for Multiple BI Applications Are Burdensome. Finally, IT organizations suffer excessive redundant costs in managing many diverse BI technologies. With multiple BI tools, companies need to train people in the development and operational intricacies of each BI technology. Companies must establish technical support teams to specialize in each capability. Companies must manage contracts with each BI vendor. Companies must go to conferences, user groups and support forums for each BI vendor. Companies must coordinate

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore new version upgrades with their versions of database software, server operating systems, workstation operating systems, browsers, web servers and firewalls. Companies must manually synchronize metadata overlaps between multiple BI technologies – such as security, business definitions, metric definitions and user profiles. Only with a single BI architecture can a company avoid all of these redundant costs and efforts. Only the MicroStrategy architecture can deliver all 5 Styles of BI with the enterprise scale of data and user populations, in turn freeing up time, effort and money.

I. The Ideal Architecture for Delivering All 5 Styles of BI The ideal architecture for delivering all 5 Styles of BI is one that can deliver: 1. Any or all Styles of BI which can be mixed-and-matched seamlessly for the end users, where the addition of each new BI Style adds functionality to the users’ existing reports 2. All expressed through a single unified user interface to maximize ease of use and user acceptance 3. All delivered on top of a single integrated backplane that unifies the metadata, security and user profiles, ensuring a single version of the truth throughout the enterprise and thus minimizing administration and maintenance efforts by IT The MicroStrategy architecture was completely rebuilt from the ground up from 1996 through 2000 to achieve precisely this range of flexibility, along with unparalleled scalability – all the things that companies need for industrial-strength BI.

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The MicroStrategy architecture stands alone in the BI market space as the one integrated architecture, built from the ground up to deliver all 5 Styles of BI with the level of scalability and manageability suitable for enterprise BI applications and capabilities.

A. Enterprise Reporting: Enterprise Reporting is designed for information consumers; individuals at all organizational levels and across all job functions in the enterprise and also include supply chain partners and even customers. Enterprise Reporting, in essence, provides business intelligence to the masses.

As a result, it is the most prevalent Style of BI, encompassing a vast array of operational reporting directly from ERP an CRM systems, as well as scorecards and dashboards of overall business performance.

The single most dominant characteristic of any Enterprise Reporting system is its ability to produce highly flexible report formats, so that data can be presented in whatever form is most consumable to a wide range of information consumers. These individuals get their reports by accessing them on-demand through their Web browsers (web-based reporting), as well as by receiving distributions that are pushed to them via email or print delivery.

Enterprise Reporting technologies revolve around the following key areas: 1. Support For All Forms of Enterprise Reports – From scorecards and dashboards at one extreme, all the way to operational reports at the other extreme, and the many variations in between. Report writing products typically either can deliver operational reports well or can deliver scorecards and dashboards well – but not both. MicroStrategy’s advanced architecture is

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore designed to deliver both operational reports and scorecards and dashboards easily from a single platform. In fact, MicroStrategy allows users easily to develop the five common forms of enterprise reports that range from highly graphical Scorecards and Dashboards for executives to densely populated tabular Operational Reports for all personnel. In between these extremes are Classic Business Reports for business unit managers, Managed Metrics reports for business unit leaders and Invoices and Statements for customers and partners.

Delivering The Five Common Forms of Enterprise Reports – Ranging from Scorecards and Dashboards to Operational Reports Report Form 1 – Scorecards and Dashboards for executives: Scorecards and dashboards (Fig. 6) are designed to deliver maximum visual impact to the user in a format optimized for quick absorption. MicroStrategy scorecards combine tables, graphs, gauges and other graphical indicators, conditional formatting, free-form labels, borders and background colors to achieve this impact.

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore Report Form 2 – Operational Reports for all personnel: The vast majority of enterprise information dissemination is in the form of traditional Operational Reports (Fig. 7). These timetested reports display volumes of tabular data organized into a hierarchy of increasingly finer levels of detail.

Report Form 3 – Classic Business Reports for business managers: MicroStrategy’s free-form layout may be used to create popular business reports, such as P&L reports, performance reports and statutory reports. These reports are usually optimized for on-screen viewing and allow the user to drill to deeper details and related reports. Classic Business Reports (Fig. 8) easily combine tables, graphs and freeform field layout to create unique presentations of summary and detailed data.

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore Report Form 4 – Managed Metrics Reports for business unit leaders: The drive to manage business “by the numbers” and deliver predictable results has lead to a renewed interest in Corporate Performance Management, or CPM. The cornerstone of CPM is the Managed Metrics Report (Fig. 9), which allows managers to track continually the status of business performance, including actual-to-planned comparisons, time series projections and process flow analyses. With MicroStrategy, this is achieved using thresholds and graphical indicators to show attainment of performance goals, trends over time and status checks to manage to the metrics or targets. By incorporating predictive analysis native to the MicroStrategy platform, these reports can also display correlations and projections to help anticipate future business performance.

Report Form 5 – Invoices and Statements for customers and partners: Invoices and Statements (Fig. 10) contain detailed transactional data and summarized information for any number of customers and partners. This enterprise report form is designed with page layout precisely defined and report elements precisely formatted and positioned to ensure proper printing across multiple sheets and with pre-printed corporate stationery. To generate Invoices and Statements, MicroStrategy uses the same exacting page layout techniques as those used by desktop publishing packages.

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B. User-defined Web Reporting The goal of every Enterprise Reporting project is to inspire people to use information in their day-to-day work activities. However, most projects fail to achieve this goal because the reports are not immediately relevant to each recipient user – that is, a user must sift through reams of numbers to find just the few sections that directly relate to his or her area of responsibility. The other reason reporting efforts fail to achieve their goals is because the Enterprise Reporting environment is not easily tuned to the diverse skills of a wide population of users – that is, the user interface is either too simple and appeals only to the most novice users, or it is too “feature-rich” and overpowers the novice users.

This is a very difficult technical challenge and most BI products fail miserably because they do not give the people enough control over the report contents and their Enterprise Reporting environment, nor do these products automatically tailor report content to fit the users interests and skill. MicroStrategy was designed specifically to solve this problem through four personalization levers: Parameterized Reporting – Letting the User Define the Report Contents

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore Parameter-driven reports allow the user to answer a number of questions prior to running a report, and those answers dictate what content will be displayed in the report. It allows a user to generate just the data they are interested in seeing at that moment. For example, users may answer prompt questions such as “Which product would you like to analyze,” and “Over what period of time,” and “In which geographical areas,” and “For which customers.” This is the basic idea behind parameterized reporting, and many report writing products offer this basic level of user control.

MicroStrategy has taken the basic idea of parameterized reporting and user prompting – and elevated it to new levels of user control.

Automatically Customized Content – Allowing One Report to Serve The Needs Of Thousands Of Users Automatically Through Role-based Content A common challenge in Enterprise Reporting is how to deliver similar information to very large populations of users economically, where each user needs to see a different slice of the data. The traditional solution is to provide each user with a custom-designed report. Clearly this is a nightmare for the report designers because one small change needs to ripple through many renditions of the report. With MicroStrategy, IT administrators only need to create one report that the system automatically slices into the different views appropriate for each individual user. In addition, MicroStrategy content slicing takes place along any number of business attributes based automatically on each user’s role and group affiliations.

Personalized User Interface Based on User Profile – Matching User Interface Functionality Level With User Skill Level Enterprises face a challenge when striking a balance between exposing rich functionality to power users, while at the same time giving novice users a simple Enterprise Reporting environment that will not overpower them. MicroStrategy is designed to solve this problem elegantly through the user of user profiles.

User profiles automatically adjust the Web interface to accommodate users with different skill levels. User profiles determine exactly what functionality will be exposed to each user or user group (Fig. 15). So it’s easy in MicroStrategy to give report designers a user profile with maximum functionality, while the report consumers receive a user profile with just enough functionality to do their jobs easily.

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C. Multi-lingual Support Enterprise Reporting must span the globe with reports personalized to the local languages in which they are accessed. With MicroStrategy, users can access their Enterprise Reporting environment in twelve different languages out-of-the-box: American English, British English, Chinese (Traditional), Chinese (Simplified), French, German, Italian, Japanese, Korean, Portuguese, Spanish, and Swedish. MicroStrategy report translation includes all of the interface items like menu bars and online help. It also includes character sets, currency formats, time and date formats, and even business attributes and metrics in the report .

High Throughput Report Production and Distribution

Information consumers are everywhere. They are in executive offices, in office cubicles, on warehouse floors, at loading docks, at customer sites, at suppliers’ offices, and at customers’ homes. Effective Enterprise Reporting systems must be able to reach all of these users, wherever they are and with sufficient power to generate tens of thousands of reports per hour if needed.

The MicroStrategy architecture sets the standard for high volume, high flexibility report distribution.

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore MicroStrategy reports can be automatically distributed to the widest range of user touch points on the market, including Web browsers, networked printers, email, networked file servers, and corporate portals MicroStrategy reports can be delivered directly to any Web browser, both inside and outside the corporate firewalls because MicroStrategy is the only vendor employing a true zero footprint Web architecture, which requires no downloads, ActiveX, or cookies.

MicroStrategy’s unified Web interface is proven efficient and effective with user populations in excess of 100,000 individuals internal and external to the enterprise. MicroStrategy reports can also be printed in a batch production mode. This is a mode where every individual print job might be directed to a different networked printer that is associated with each recipient user. And, the content will be automatically personalized to each recipient on his or her printer.

II. CUBE ANALYSIS Cube Analysis delivers the simplest form of analysis, allowing anybody to analyze data. Cube Analysis is used most often by people like managers who have a deep interest in understanding the root causes underlying the data in reports, but do not possess skills for full ad hoc investigation of the databases. Cube Analysis lets people flip through a series of report views, using the now standard OLAP features of: page-by, pivot, sort, filter, and drill up/down. These OLAP features, which were first introduced in the early 1990s, allow users to slice-and-dice a

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore cube of data, or analysis cube, using simple mouse-clicks. The term “cube” refers to a subset of highly interrelated data that is pre-organized to allow users to combine any attributes in the cube (e.g. stores, products, customers, suppliers) with any metrics in the cube (e.g. sales, profit, units, age) to create various 2-dimensional views, or slices, that can be displayed on a computer screen.

MicroStrategy’s Intelligent Cubes provide all of the same OLAP functionality that small-scale MOLAP cubes provide, but with significant enhancements available only with a ROLAP underlying architecture.

Speed-of-Thought Report Analysis and Manipulations MicroStrategy’s Intelligent Cube technology lets users perform report manipulations on a multidimensional cache of data rather than a limited, proprietary cube database. These caches are instantly populated by the simple action of “running a cube” and remain in shared cache for as long as the data is valid and people are using it. This eliminates the entire IT overhead imposed by managing cube farms.

Intelligent Cubes Provide Speed-of-Thought User Information Intelligent Cubes give users a much greater range of functionality. With Intelligent Cubes, people can quickly add or remove report objects and modify report-filtering criteria with drag-and-drop actions in the Web interface. Additionally, users can add new calculations or modify existing

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore calculations on the fly with an Excel-like formula bar, utilizing the full power of MicroStrategy’s Library of Statistical and Mathematical Functions.1 All of these convenient user actions – adding/removing objects to/from a report, filtering a report with new criteria, and creating new metrics – do not require going back to the database and are performed with speed-of-thought response time.

Minimized Administrative Costs and Workload MicroStrategy automatically creates Intelligent Cubes when users view or edit reports.

MicroStrategy empowers users to create and modify their own cube definitions at any time, from any Web browser, and without administrative help. Users create and modify cube definitions by simply dragging-and-dropping report objects, such as business attributes and metrics. At that point, MicroStrategy automatically generates optimized structured query language (SQL) to create the Intelligent Cube. MicroStrategy intuitively uses the appropriate Intelligent Cube or creates a new Intelligent Cube on the fly to satisfy any user’s ad hoc request.

Users can modify existing Intelligent Cubes by adding or removing business attributes and metrics from across all enterprise business dimensions or creating new calculations on the fly from existing metrics in an Intelligent Cube. The new calculation is performed without submitting a new request to the database. Users can also filter their view of the data within an Intelligent Cube.

Cube Sharing with Personalized Views and Security IT administrators struggle with maintaining and managing multiple cubes with duplicated data across user desktops, Web servers, file servers and other locations. The architectures of other BI software spread data across multiple systems within the enterprise. Consequently, users are at risk of analyzing outdated data on their desktops and using different analytical definitions of the same business terms due to decentralization of information across physical cubes of data. Thus, cubebased BI users cannot reliably share insights because dissimilar numbers can show up on the same report definitions.

Easy Sharing Of Intelligent Cubes Data With Centralized Metadata and Server Architecture Only the MicroStrategy architecture is structured on a centralized and unified metadata that stores all business terms and data warehouse object definitions in one location. All information about

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore reporting and analysis applications, users, reports, metrics and filters are stored in the metadata and can be shared by all users through the MicroStrategy architecture’s centralized server. When an administrator creates a new Intelligent Cube, all users can access it instantaneously. Business terms and definitions are standardized across the enterprise. When multiple users with the same security levels run the same report, they get the same data. These users can also share this information easily with other internal and external users simply by saving the reports in a shared folder. Since these shared folders are also stored in a central location, all system users can easily access saved reports over the Web or on the Windows desktop. Additionally, users can email reports directly from the Web. Sharing Intelligent Cubes Data With Personalized Views When analyzing Intelligent Cube data, users can add, edit and remove business attributes and metrics. These actions result in various personalized views of the same Intelligent Cube. Users can then save these views so that the next time they run the Intelligent Cube, it will reflect their personal view. Thus, a report designer can deploy one Intelligent Cube shared y all users, each with a personalized view. Hence, all personalized views are logically linked to the single published report; and, regardless of the view, all users are accessing the same upto-date data.

Secure Sharing of Intelligent Cubes IT administrators can be assured that Intelligent Cubes are shared securely because they use MicroStrategy’s same multi-tiered security that applies to all Styles of BI with MicroStrategy. As a simplified example, an administrator can design a report with ten business attributes and metrics. Both John and Martha can share the same Intelligent Cube data, but Martha can view all ten objects and John can view only six of the ten since his security profile denies him access to the additional four objects to which Martha has access.

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III. AD HOC QUERY AND ANALYSIS Ad Hoc Query and Analysis is the Style of BI designed for information explorers and power users who need full investigative power against all enterprise data. These users require the ability to see any possible combination of data. If it were feasible to pre-design reports that covered every possible combination of data, then Ad Hoc Query and Analysis would not be needed.

Practically speaking, this is impossible. Pre-defining reports with all possible permutations would require the design tens of thousands and even millions of reports depending on the extent of the database. It would also require the addition of hundreds or thousands of new reports each time a new attribute is added to the database. The MicroStrategy architecture was designed from its very roots to provide the most robust Ad Hoc Query and Analysis capability in the industry. The MicroStrategy architecture allows users to create their own new ad hoc reports using the entire relational database as the source. MicroStrategy is founded on the Relational OLAP technology that allows users to perform full OLAP analysis against the entire relational database. The MicroStrategy architecture distinguishes itself from all other BI architectures in key areas of Ad Hoc Query and Analysis application:

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Business Intelligence And It’s Use In Decision Making� At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore Parameter-driven Reporting and Guided Analysis Parameter-driven reporting functionality allows people to customize the content and layout of any given report within a range of variations defined by certain factors or parameters. The MicroStrategy architecture provides the richest range of parameterization available, allowing one report design to manifest itself in more variations than with any other BI technology.

Customizing Report Content Based on User Input at Run-time With MicroStrategy, novice users can create sophisticated custom reports on the fly, defining report content by selecting metrics and business criteria at run time – simply by answering prompted questions. This allows enterprises to translate complex database query parameters into a set of simple questions that guide users

Ad Hoc Report Permutations By Varying User Inputs What makes parameterized reporting truly useful is when the users have the ability to iterate quickly through many parameter sequences and to save their sequenced answers for future use.

Users can re-run the same report with different parameter combinations as they refine their analysis. Furthermore, the basic analytical workflow is embedded in the parameter sequence as a series of hierarchical questions. Once a user has identified a truly useful report based on a set of

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore specific prompt answers, he or she can save that report with the prompts already answered in exactly the same way, thus generating a new ad hoc report. This lets each user save a full set of new reports that are simply useful pre-defined combinations of one parameterized report.

Ultimately, through this process, the users get to decide which parameter combinations are useful through their actual day-to-day work, and can save the most useful combinations for future use and sharing across a workgroup or the enterprise.

Drill Anywhere Allows Users to Surf the Entire Database, Creating New Ad Hoc Reports Dynamically Through the Drilling Process MicroStrategy users can surf the full range of enterprise data with an intuitive right-click drilling menu (Fig. 28). For example, they can drill from the quarterly regional sales to the customers’ daily transactions at individual stores. From there, users can drill to the most profitable customers who shop in that particular store and to the products purchased by these profitable customers for cross-selling opportunities. The process for moving down or up a hierarchy to more- or lessdetailed data is commonly called drill down and drill up, respectively. The capability to shift to other hierarchies – for example, replacing customer with supplier – is called drill across.

Collectively, the ability to perform any one or combination of drill down, drill up, and drill across actions – at any level of detail, anywhere in the database – is referred to as Drill Anywhere.

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IV. STATISTICAL ANALYSIS AND DATA MINING Statistical Analysis and Data Mining is targeted at professional information analysts, individuals who regularly perform correlation analysis, trend analysis, and projections. This advanced Style of BI is achieved by applying mathematical, financial and statistical functions against enterprise data. The business insight derived from Statistical Analysis and Data Mining is critical for every enterprise. However, specialized data mining tools are difficult to use – only statisticians with technical training are able to use them. Instead, MicroStrategy’s BI technology was designed specifically to deliver much of the common functionality of data mining tools – and to deliver it in a way that is familiar and consistent with everyday business intelligence usage.

MicroStrategy’s Statistical Analysis and Data Mining features include the following Applying Statistics and Data Mining Against the Entire Database and for All Users – Using MicroStrategy’s Comprehensive Library of Statistical and Mathematical Functions MicroStrategy users can apply any of over 200 mathematical, OLAP, financial, and statistical functions against the entire volume of data collected in the enterprise data warehouse. The MicroStrategy architecture accomplishes this through its highly sophisticated SQL Generation Engine as well as by its specialized Analytic Engine that supplements the database’s calculation capabilities. By contrast, other BI technologies have far fewer native functions than MicroStrategy, and those functions can only be applied to the limited data volumes present in proprietary cube databases. Due to their inherent data limitations, cube-based BI architectures are incapable of providing a comprehensive picture of the inter-relationships of data across the enterprise.

For example, telecommunications and financial services enterprises log millions of records every day. These enterprises can only gain insight into their records if they can directly access the transaction level data. One MicroStrategy telecommunications customer discovered new insights into customer calling patterns, resulting in cost savings of tens of thousands of dollars every

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore month. This level of analysis and subtlety of insight could not be detected in the usual aggregated monthly analysis typical of cube-based BI tools.

Plug-and-Play Architecture for Custom Analytical Functions Many enterprises have unique and proprietary calculations that are needed because of the unique and proprietary character of their business model. Whether it’s some unique calculation of productivity, or a unique correlation formula relating sales to promotions, or price elasticity coefficients, all companies have some business calculations that are not simply standard mathematical functions. Interestingly, these also tend to be some of the most critical business questions that a BI system should be able to address. This is where custom analytic functions become very important.

MicroStrategy’s Extensible Architecture For Plugging in Custom-built Functions The MicroStrategy architecture is open and extensible, allowing enterprises to create their own custom analytic functions, and embed those functions in any BI report or analysis (Fig. 34).

MicroStrategy accomplishes this using a step-by-step Plug-In Wizard to make it simple for average people to create new analytics for the enterprise or their workgroups. Once a custom analytic function is added to the MicroStrategy Library, it can be used just like any other function. Users do not need to learn multiple tools to achieve their analysis goal.

Seamless Integration with Data Mining Tools The main purpose of data mining is to discover patterns and algorithms in the existing data that can be used to predict future outcomes. This includes analysis techniques such as regression, segmentation, clustering, and forecasting. Typically, whenever business users need sophisticated predictive functionality, they must contact a highly skilled developer to assist with their request using a formal data-mining tool. Mathematicians, statisticians and administrators then “discover” the appropriate algorithms using data mining tools along with a subset of the actual data by “training” the data-mining tool. Unfortunately, a recurring problem with this basic model is that each analysis tends to be a one-time event. That is, the new algorithms are not generally available to all users through their standard BI reporting or analysis system– instead the separate data mining processes delivers a series of one-time answers to the requester.

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore Sophisticated Analytic Collaboration with Relational Databases The MicroStrategy Analytic Engine operates collaboratively with the calculation engines embedded in the relational database management system (RDBMS). Not all databases have the same calculation capabilities. There are some important analytical functions that some databases simply do not support and other analytic functions that database systems cannot do quickly. To overcome this, the MicroStrategy Analytic Engine automatically compensates for variations in calculation capabilities of the different database systems– allocating calculation responsibilities to the database syste when it can be best done in there, and reserving the calculation for MicroStrategy when the database system can not accomplish it quickly.

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V. REPORT DELIVERY AND ALERTING Report Delivery and Alerting is the Style of BI designed to proactively distribute large numbers of reports and alerts to potentially very large populations of information consumers – both internal and external to the enterprise. With such a broad mandate, Report Delivery and Alerting must be highly flexible and functional. Most BI vendors offer products that support a minimal form of Report Delivery and Alerting. That is, most BI vendors offer products that can centrally distribute emails to large user populations, with report enclosures, and on a scheduled basis. The MicroStrategy architecture also supports this minimal functionality, but further distinguishes itself by supporting an additional four key areas: Report Distribution Through Any Touchpoint MicroStrategy reports can be automatically distributed through the widest range of user touchpoints on the market, including email, Web browsers, networked printers, networked file servers, and corporate portals. With email distribution, MicroStrategy can display the report contents directly in HTML, or can enclose the report as an attachment in the form of an Excel, Rich Text Format (RTF), or Portable Document Format (PDF) file. And with MicroStrategy, these attachment files can automatically be zipped and password protected. With networked printer distribution, reports can be sent directly to networked printers around the world automatically. The report is formatted in the print-perfect PDF format and sent to all of the printers defined by each recipient user’s preferences. With networked file server distribution, MicroStrategy can distribute reports directly to archival file servers anywhere on the network. With each new file distribution, the system can automatically create new archive folders, thereby allowing companies to keep a historical record of all standard reports. With corporate portal distribution, MicroStrategy can distribute reports directly to Web portals. This allows companies to concentrate all information publishing and consumption on their corporate portals, thereby offering a one-stop-shop for all standard company information.

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Business Intelligence And It’s Use In Decision Making� At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore Self-subscription as well as Administrator-based Distribution All competent Report Delivery and Alerting technologies are able to distribute reports when a central administrator manages the entire distribution process. In this case, the central administrator establishes all distribution services and assigns all users to receive various reports at various times. Any user who wants to be included in a weekly report distribution contacts the central administrator and requests to be put on the distribution list. Obviously this model has severe practical drawbacks as the number of users gets very large, as each user has a different distribution profile, and as users continually add and delete reports from their distribution profile. The central administrator becomes the central bottleneck. MicroStrategy avoids this problem by also allowing users to self-subscribe to reports – without the need for any administrator intervention. This eliminates the dependence on a central administrator and allows users to continually change which reports they want to receive and when. With MicroStrategy, end users even have the ability to subscribe other end users to receive reports too, so a manager can subscribe her subordinates to receive a weekly report that she deems important for her group. Self-subscription over the Web with MicroStrategy greatly reduces administration costs while enabling applications to be deployed to extremely large user communities. For example, an IT administrator can create one parameterized report and instantly deploy it to all users, letting each user customize the report with his or her own parameters instead of designing and sending unique reports individually to each user. Moreover, centrally maintained MicroStrategy security profiles ensure that users do not receive any information to which they are not entitled.

Delivery On-demand, On-schedule or On-event MicroStrategy users and administrators have complete control over the timing of all their report distributions. In the simplest case, users and administrators can establish a periodic distribution for any report (on schedule), such as every Monday morning at 8:00 AM, or every other Tuesday, or the first Friday of every month. In addition, users can establish subscriptions for themselves as well as establish them for other people as long as they have the security privilege allowing them to do so. Users also have the ability to distribute a report to others immediately (on demand). In this scenario, a user freely can customize a report with pivoting, page by, drill anywhere, etc. and then immediately send that report result to any other user of the system. The recipient will see exactly the report that the sender saw prior to sending Finally, MicroStrategy report distributions can be triggered based on an event that occurs in the database itself (on event). This might include new data being loaded into the database or even

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Business Intelligence And It’s Use In Decision Making� At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore something as precise as a metric in the database exceeding some pre-established threshold value.

The event-based distribution capability is critical for real time alerting applications.

Automatic Content Personalization One of the biggest problems with any report distribution system is making large amounts of general information relevant to all recipients. Most people are only interested in a small slice of data contained with-in a standard report. That slice might be one product, or one region, or one time period. But each recipient receives all data on all products, for all regions, and for all time periods because that’s the way the report was generically designed. MicroStrategy avoids the common pitfalls of generic reports by providing four levels of content personalization, ensuring that content is automatically personalized for each recipient.

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore

Conclusion: The MicroStrategy architecture is unique in the BI industry.

• It is the only architecture that supports all 5 Styles of BI in a mix and match fashion, allowing customers to implement just the functionality they need, whenever they need it.

• It is the only architecture that delivers all 5 Styles of BI through a unified user interface that is simple enough for novice users, and powerful enough for the most advanced users.

• It is the only architecture that delivers all 5 Styles of BI on a single unified backplane that ensures rapid development time, minimum maintenance effort, a single version of the truth throughout the enterprise, and 24 x 7 operation.

Ultimately, the MicroStrategy architecture is future-proof. Companies can start small with limited functionality and limited scale, but can grow to include all BI functionality, with the highest scalability, highest performance and best reliability.

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore Esporta Passes Fitness Test with New Technology to Gain and Retain Members Esporta Health and Fitness, the premium family fitness and racquets operator identified that improved IT would help its 66 clubs generate and retain more individual and corporate members. Solutions provider DPR Consulting developed a Business Intelligence solution based on Microsoft data mining technology. It is enabling Esporta to take a single view of its customer base and make better decisions regarding its marketing spend. The health and fitness operator is now equipped with better knowledge of its customers’ behavior enabling more informed decisionmaking.

Situation For a rapidly growing industry like health and fitness, customer information has largely been difficult to get hold of. Convincing busy people to take time out to go to the gym is one challenge, but finding ways of keeping them at a club is nearly impossible without a good understanding of who they are.

With 260,000 members at 66 clubs, Esporta knows how hard this can be. Esporta had two problems. First, the health and fitness chain had no accurate data on how long it took to turn a prospect into a customer, or how to accurately measure the costs involved. It spent a great deal of time and money on marketing campaigns, without having any reliable insight as to whether or not they were working.

Nick Moran, Group Sales Manager, Esporta, says: “We couldn’t make accurate, informed decisions on which to base our marketing spend. While we could pull together basic marketing reviews, we had no visibility in terms of where certain membership enquiries were coming from.”

Esporta needed a solution that would allow it to measure marketing timescales, speed, and success of campaigns, and use these figures to generate new sales and marketing campaigns.

Second, the club needed a better view of its customers to understand their habits, establish the customers likely to remain at the club, those showing signs of leaving and so on. “We were reliant on accuracy of information sent through in a prompt and timely fashion from our clubs,” says Moran. “This was not good use of our time or their time and slowed the process down.”

One of Esporta’s potential business areas is corporate membership. But Esporta was unable to understand which companies their members worked for as much of this information was

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore decentralized. As a result there were clear risks in permitting certain clubs to offer corporate memberships for fear of a dilution of membership income.

Solution Esporta called on solutions provider DPR Consulting to help it develop a Business Intelligence solution, based on Microsoft® SQL Server™ 2000 Analysis Services integrated server software. This solution, called ‘First Contact’ went live in April 2002.

“We went to DPR as I was pleased with the work they have done for me in the past,” says Jon Forster, Group Head of IT, Esporta. “We were looking for a Microsoft solution as the case studies I’d seen were positive and we wanted to standardize on a Microsoft platform to support any future technological developments.”

First Contact is a contact management system, which enables users to monitor a single view of customer data from all 66 clubs. It takes data from the organization’s existing ACT! contact management system and uses Data Transformation Services to deliver it into SQL Server.

Using a simple ProClarity interface and Microsoft Excel, users can analyze this information via Microsoft Analysis Services—a powerful way of analyzing data without restriction. Multidimensional data representations called online analytical processing (OLAP) cubes enable the sales and marketing team to look at customer data from multiple viewpoints. It is possible to ‘slice and dice’ the cubes of information to get different views of data quickly.

Dan Wakefield, Microsoft Solutions Director, DPR, says: “We gave Esporta an analysis system that tells it how successful its marketing campaigns are and how much they cost. It enables the organization to market more effectively, knowing that there is a bit of science behind it.”

Phase two of the solution, which went live in April 2003, is a Membership Analysis System— used by sales and marketing to assist in retaining customers. It determines the habits of its members, such as those who are most profitable, their routines, and behavior.

“Esporta can forecast what it needs to do to keep the membership levels up,” says Wakefield. “It can forecast the member ‘drop-out’ rate and drive a new campaign aimed at replacing them.”

The creation of a second information cube allows the 66 clubs to report like-for-like figures on

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore corporate membership at a touch of a button. This enables the company to establish how many members work for one organization and compare this across the whole estate. Esporta can now evaluate the potential for membership growth by offering a wider corporate scheme to UK wide organizations, helping the business and its members.

The solution takes data from the organization’s DRL membership system—which holds all membership details—and delivers it via Data Transformation Services to SQL Server Analysis Services.

Benefits Saving Costs through Better Marketing Esporta has already reaped the benefits of implementing the First Contact solution—using the data-mining

tool

to

identify

marketing

issues

that

need

addressing.

Forster says: “We used to spend thousands and thousands on certain types of marketing. We don’t do that any more, as we are better at judging whether or not these decisions will be effective.”

Moran says: “We have definitely saved money. Before the implementation we adopted a semieducated ‘finger in the air’ approach. We have had a number of campaigns over the years where we believed that the mediums, strap-line, or creative messages were appealing. But that wasn’t necessarily so.

“For example, newspaper advertising may work for some clubs but not others. Now we can monitor the number of enquiries that have been made through the local newspaper, and compare it with the number of sales that have been made against it. We know for sure that this form of marketing

works

in

some

parts

of

the

country

but

not

in

others.”

Wakefield says: “With the help of Microsoft technology we have saved Esporta a fortune in marketing. They have abandoned a whole range of marketing activities because the system showed they weren’t working.”

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore Boosting Staff Efficiency and Productivity Prior to the use of SQL Server, Esporta clubs spent hours phoning around to collect the data about new members. Wakefield says: "Analysis Services enabled Esporta to exploit the product they already had. They didn’t want to buy a new system—they wanted to use what was already there.”

Forster says: “Staff members would have the telephone pressed to their ears for several hours. As we’ve grown rapidly from 30 clubs to 66 clubs, it would potentially take a whole day. Now when they arrive in the morning, the information is already there. This solution changes the way people work.”

Using the solution, Esporta can identify which clubs need to focus more on their marketing.

Moran says: “Immediately we can see if a certain club, which has collected 300 new names and addresses, still has unqualified leads. I can go and speak to that club with new objectives.

Everyone can see the value in getting it right, all the way down the chain.”

Precision Decision Making The membership analysis ensures Esporta can better identify its clients and establish patterns in its

membership.

Forster says: “We can look back and see how long someone has been a member. We can estimate who’s going to leave, who’s going to stay, and for how long. The solution moves us away from using information that was based on a gut feeling, to something that is now based on fact. We can make sure that our marketing makes an impact, instead of just hoping that it will.”

Moran says: “We have 260,000 members and we need to understand how they behave. These systems help us target similar member groups in the future. Looking back and understanding more about members’ habits, and marketing more cleverly are the best ways to gain value from our marketing pound.”

Giving Customers the Best Deal The solution enables Esporta to develop its corporate memberships. It can instantly see how many members work for the same company. “We can then make good decisions on whether we can

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore offer that company a better rate,” says Moran. When new companies make enquiries, Esporta can quickly establish if individual offices have already set up local arrangements and negotiate with them

to

either

bring

them

all

together

or

continue

as

they

are.

“We are trying to sell people the chance to change their life—a decision that exists entirely in their own minds,” says Moran. ” We also understand that new members are often more active at the beginning and then ease off. At that vital early stage we can inspire them to get back into the exercise habit, rather than try and recover them when it’s too late. We can help members achieve their own aims.”

Flexibility for the Future Esporta is delighted with the way the Microsoft technology is scalable to grow with the organization. “One of the reasons for going down the Microsoft route is that we can build on it,” says Forster. “I don’t have to waste the money I’ve already spent on it just to add new technology when the time is right.

“We now understand a lot more about what Microsoft Analysis Services and ProClarity are able to do for us, so we will be more sophisticated a year down the line, and will have a better idea of what we want to do in the future.”

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FUTURE OF BUSINESS INTELLIGENCE

Future of Business Intelligence – Visitionaries Note : 

In five years, 100 million people will be using an information-visualization tool on a near-daily basis. And products that have visualization as one of their top three features

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore will earn $1 billion per year. -- Ramana Rao, founder and chief technology officer, Inxight Software Inc., Sunnyvale, Calif.



Within three years, users will begin demanding near-real-time analysis relating to their business -- in the same fashion as they monitor stock quotes online today. Monthly and even daily reports won't be good enough. Business intelligence will be more focused on vertical industries and feature more predictive modeling instead of ad hoc queries. -Thomas Chesbrough, executive vice president of Thazar, a Skywire Software company, Frisco, Texas



In the next three years, companies (and their business managers) will become utterly dependent on real-time business information, in much the same way that people expect to get information from the Internet in one or two clicks. This instant "Internet experience" will create the new framework for business intelligence, but business processes will have to change to accommodate and exploit the real-time flows of business data. -- Nigel Stokes, CEO, DataMirror Corp., Toronto



Companies are drowning in terabytes of data. In order to exploit the growing ocean of data, businesses will focus their business-intelligence spending in the next three years on technologies that address the inefficiencies of the underlying data storage, rather than the already powerful analytic applications. -- Foster Hinshaw, chief technology officer, Netezza Corp., Framingham, Mass.



In the next two years, business-intelligence capabilities will become more democratized, with a far greater number of end users across the enterprise using the tools to get better visibility into the performance of their segment of the business. Think of it as executive dashboards for worker bees. -- Steve Molsberry, senior consultant, Stonebridge Technologies Inc., Dallas

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore 

By the end of next year, banks will rely more and more on information gleaned directly from customers to predict loan defaults and collections. Lenders will use notes from customer interactions and conversations with collection center agents, as well as e-mail and other streams of unstructured communication, to significantly improve the prediction of the customer behavior. Banks currently rely on historical structured transaction data that's only producing marginal returns. But higher write-off rates and debt delinquencies will force financial institutions to deploy new methods. -- Gwen Spertell, CEO, Intelligent Results Inc., Palo Alto, Calif.



By improving the targeting of marketing messages, business-intelligence technology may save more than $200 billion dollars a year in wasted advertising and direct marketing.

Data mining combined with marketing automation changes the fundamental economics of marketing and will probably increase the efficiency of all marketing expenditures by as much as 20% by 2007. -- Dave Morgan, CEO, Tacoda Systems Inc., New York



Business is war! Like in any war, survival depends on being able to act quickly in a constantly changing environment. Business intelligence will eventually operate as a business command-and control-center (BCCC). Similar to how a missile command center constantly performs tracking and analysis and triggers countermeasures, the BCCC will track variables, such as operational performance, market conditions and competitors' performance, in real-time. -- Sol Klinger, director, Sterling Management Solutions Inc., Princeton, N.J.



Unstructured customer feedback contains critical indicators for customer attrition, upsell opportunities and product enhancements. In 2003, companies that fail to utilize their customers' unstructured feedback will be left in the dust! -- Guy Jones, vice president and founder of Island Data Corp., Carlsbad, Calif.



By 2006, half of all data warehouses that exist today will be replaced by a more streamlined architecture that I will call "data shopping malls." They'll contain sets of data

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore arranged by use for each business unit that will allow the business-unit managers to analyze data specific to their area of interest. The data shopping malls will be more accurate, more responsive and less susceptible to the statistical anomalies of large data sets in the data warehouse. -- Craig Branning, senior vice president, Tallan Inc., Glastonbury, Conn.



Knowledge workers have tended to analyze data in isolation because the software they use doesn't let them do anything else. But data analysis must move from solo to collaborative if we're ever going to eliminate the bottleneck of specialized business analysts. This means packaging analytical applications into portal interfaces that ordinary people can access online and then allowing them to share not just the static output, but [also] the actual dynamic analytical experience through online collaboration. We'll see this happen among early adopters later this year, and it will be mainstream by 2005. -Andrew Coutts, CEO, Databeacon Inc., Ottawa



Within two to three years, companies will ditch the traditional model of making business adjustments on a quarterly basis. Instead, they'll use business intelligence and performance management tools to make real-time shifts in strategy to respond to changes in the marketplace. --Rob Ashe, president and chief operating officer, Cognos Inc., Burlington, Mass.



Vendors that promise business intelligence but capture only historical data from company databases will be tomorrow's memories -- extinct providers who simply couldn't deliver true real-time intelligence. Real business intelligence means analyzing not only documents, databases and e-mail, but also other sources of rich and constantly changing data, such as Web site content, PDF files, Internet-based discussions, call logs and survey responses. -- Mahendra B. Vora, chairman and CEO, Intelliseek Inc., Cincinnati



Within five years, terms such as business intelligence and data mining will have all but disappeared from the corporate lexicon. They'll be replaced by business actions

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Business Intelligence And It’s Use In Decision Making” At TARANG SOFTWARE TECHNOLOGY LTD, Bangalore automatically triggered by systems with "corporate foresight," based on predictive analytics. And instead of being used by a limited number of technical analysts, these technologies will be applied at all levels, from the CEO managing corporate risk to the human resources professional identifying attrition risk among the best employees. -Colin Shearer, vice president of customer analytics, SPSS Inc., Chicago



Users will demand more integration between the numbers and the commentary. At some point, all business-intelligence applications will include content management or knowledge management tools as well. -- Brian Hartlen, senior vice president, Comshare Inc., Ann Arbor, Mich.



In about five years, we'll see a dramatic 40% increase in the number of end users who use business-intelligence tools. The monolithic data warehouse strategies will be replaced with technologies that build virtual data access points based on the end user's query needs. These points will dynamically collect data from a variety of sources including data mart, data warehouse, production systems and external sources and present a single personal data view. -- Frank Gelbart, CEO, Appfluent Technology Inc., Arlington, Va.



In early 2004, some bored geek starts an open-source OLAP [online analytical processing] initiative. Suddenly, Oracle doesn't think that Linux and its ilk are that cool anymore. -- Gerald Boyd, director of research, NCS Technologies Inc., Piscataway, N.J.



In a few years, competitive advantage will come from using business intelligence to understand customer behavior and preferences at a narrow segmentation level and even an individual level and then delivering customized, context-sensitive offers. But given the cost and difficulty of actually doing this, by 2010, at least 50% of the Fortune 500 will turn to outsourcing contractors that have the next-generation technology and database marketing expertise to do it. -- Jeff Zabin, vice president, Seurat Co., Boulder, Colo.

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Bibliography:

WEBSITES: 1. www.microstategy.com 2. www.binews.com 3. www.businessintelligence.com 4. www.businessobjects.com 5. www.informationbuilders.com 6. www.intelligententerprise.com 7. www.wipro.com/itservices/datawarehouse

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BOOKS:

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