From the Excel you know to the Excel you don’t! Microsoft Business Intelligence Discovery Session
Amber McCormack Marketing Executive amber.maccormack@contentandcode.com
Welcome We appreciate your feedback Welcome
From the Excel you know to the Excel you don’t! Microsoft Business Intelligence Discovery Session
Ian Macdonald & Jes Kirkup BI Practice Lead Senior BI Consultant Ian.macdonald@contentandcode.com jeremy.kirkup@contentandcode.com
The Day • 09.30 - Business Intelligence Overview – The big picture
• 10.15 - The Knowledge Workers Perspective – Fact based decision making
• 11.00 - Break • 11.20 - IT and Data Management – Making sure it is right
• 12.00 - The Analyst – Deep dive discovery
• 12.45 – Summary and Next Steps
Content and Code and me Why are we here?
Content and Code 10 years building information solutions for clients Best in the world twice and top UK partner
Me & Jes 25 + 10 years designing, developing, managing and marketing Business Intelligence technologies and solutions Leading process oriented BI at Content and Code
Setting the Scene • • • • •
Your name Your role Your business pain What you need to help you overcome that pain What does “Business Intelligence” mean to you?
A Question: • Who here is comfortable with the concepts of: – – – – – – – –
• ?
Data Warehouse and Data Marts Master Data Management ETL Dimensions and Facts OLAP, Cubes and UDM Data Mining KPIs Scorecards and Dashboards
The Big Picture of Business Intelligence Goals, Concepts, and the Platform
Business Intelligence BI - Improving Business Insight
“A broad category of applications and technologies for gathering, storing, analysing, sharing and providing access to data to help enterprise users make better business decisions.� Gartner Group
demos 1.
Business Intelligence and Power of Visualisation Balanced Scorecards
Objective: Performance at a glance Complex information made easy to understand
demos What did we see? Visualisations making information come alive Easy to use, intuitive, relevant metrics across my business view As much or little detail as needed
Business Intelligence Today Low end-user adoption rates and high reliance on IT
• Analyst Issues: – Hard to access organisational data – Reliant on IT for reporting – Difficult to share insight
• IT Pro Issues: – No time for ad-hoc BI requests – Lack of control – Organisational BI often expensive
From Organisational BI to Personal BI Enabling managed self-service BI
Empowered, Managed, Accurate
IT Involvement
IT Unmanaged
IT Managed
Corporate BI
Data Data BI and Portals and Sources Marts LOB Apps Dashboards
Accurate Secure Scalable Up to date
Self Service Easy to use On and Offline Collaborative
Rogue “Spreadmarts”
User Context Reliant on IT
Empowered
Microsoft BI Strategy Democratising Business Intelligence
• Familiar environment • Integrated into Microsoft Office • Built on SQL Server Improving organisations by providing business insights to all employees leading to better, faster, more relevant decisions
Complementary BI Contexts
Personal BI Self-Service Ad-hoc Analysis
Team BI Shared, Collaborative Insight
Organisational BI Pre-designed, aligned, approved
Microsoft Business Intelligence You may already have these products Business User Experience
Business Collaboration Platform
Data Infrastructure & BI Platform
Familiar User Experience Self-Service access & insight Data exploration & analysis Integrated Content and Predictive analysis Collaboration Data visualisation Thin client experience Contextual visualisation Dashboards & Scorecards Data SearchInfrastructure and BI Platform Content Management Analysis Services Compositions Reporting Services Integration Services Master Data Services Data Mining Data Warehousing
Complementary BI Technologies
Personal BI PowerPivot for Excel 2010
Team BI PowerPivot for SharePoint 2010 & PerformancePoint Services
Organisational BI SQL Server 2008 R2
Fundamental Concepts
Enterprise Data
Silo Integration Challenge Call Center Web Apps
CRM
SOA – Enterprise Service Bus
Finance
Inventory
Data Warehouse
HR
ERP
Source Systems • Process real-time transactions • Optimised for data modifications – Normalised
• Limited decision support • Commonly called: – Online transaction processing (OLTP) systems – Operational systems HR
Finance
Inventory
Data Warehouse • Provides data for business analysis – Grouped in subject-specific stores called Data Marts
• Optimised for rapid ad-hoc information retrieval • Integrates heterogeneous source systems • Consistent historical data store
ETL: Extract, Transform, and Load 1. Extract data from the source systems 2. Transform data into desired form 3. Load data into the warehouse
ETL
Dimensions and Facts Basis of All BI
• Fact – something that happened – – – –
Sale, purchase, shipping... Transaction or an event Verb Essentially a Measure
• Dimension – describes a fact – Customer, product, account... – Object – Noun
• A fact (measure) is expressed in terms of dimensions – 42 footballs sold to John on 20100115.
Dimensions • Describe business entities • Contain attributes that provide context to numerical data • Present data organised into hierarchies
Predictive Analysis Role of Software Proactive
Data mining
Predictive Analysis Self-service Analysis Interactive OLAP
Ad-hoc reporting
Canned reporting Passive
Business Insight Presentation
Exploration
Discovery
OLAP or Multidimensional Data • Online Analytical Processing = Multidimensional Data • Measures and Dimensions • Uses a calculation engine for fast, flexible transformation of base data (such as aggregates) • Supports discovery of business trends and statistics not directly visible in data warehouse queries
Cube (UDM) Unified Dimensional Model • Combination of measures (from facts) and dimensions as one conceptual model • Rich data model enhanced by – – – – – –
Calculations Key Performance Indicators (KPIs) Actions Perspectives Translations Partitions
• Formally, cube is called a UDM
Cube Products
Cars Parts Accessories 2009 Q1
Dates
Jan Feb
Mar
Measures
Dicing a Cube Products
Cars Parts Accessories 2009
Dates
Measures
25
Q1
6
Jan
2
Feb
3
Mar
1
Ad-hoc Self-Service Analysis • Interactive, pivot-based analysis of column-oriented large volumes of data (>>millions of rows) • Pivots, advanced filtering (slicers), and tabular expressions + • OLAP-style analytics – Almost multidimensional – “Cubes without a cube in Excel”
Data Mining • Discovery of (very) hidden patterns in mountains of data • Correlation search engine • Combination of statistics, probability analysis, database technologies, machine learning, and AI
Key Performance Indicator (KPI) • Measurement comparing performance to goals • Grouped into a business scorecard to show company health – Ideally, with a balanced perspective onto groups of KPIs
• Built with: – Using OLAP (enterprise-level KPIs) – In SharePoint Server PerformancePoint Services (often team KPIs) – Using data mining (predictive KPI)
KPI Characteristics • • • •
Value Goal Status Trend
Dashboards and Scorecards • Scorecard – Table (pivot-like) of KPIs
• Dashboard – Contains scorecards, analytical reports, and other analytical visualisations
• Create them: – DIY: PowerPivot – Quickly: SharePoint 2010 PerformancePoint Services – Bespoke: custom SharePoint, Silverlight, and .NET development
Conclusions
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