MSBI, Data Warehousing and Data Integration Techniques By
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Agenda What is BI? What is Data Warehousing? Microsoft platform for BI applications Data integration methods T-SQL examples on data integration
What is BI? Business Intelligence is a collection of theories, algorithms, architectures, and technologies that transforms the raw data into the meaningful data in order to help users in strategic decision making in the interest of their business.
BI Case For example senior management of an industry can inspect sales revenue by products and/or departments, or by associated costs and incomes. BI technologies provide historical, current and predictive views of business operations. So, management can take some strategic or operation decision easily.
Typical BI Flow Users
Data Tools
Data Warehouse
Extraction
Data Sources
Why BI? By using BI, management can monitor objectives from high level, understand what is happening, why is happening and can take necessary steps why the objectives are not full filled. Objectives: 1)Business Operations Reporting 2)Forecasting 3)Dashboard 4)Multidimensional Analysis 5)Finding correlation among different factors
What is Data warehousing? A data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management's decision making process. - Bill Inmon
A data warehouse is a copy of transaction data specifically structured for query and analysis. - Ralph Kimball
Dimensional Data Model Although it is a relational model but data would be stored differently in dimensional data model when compared to 3rd normal form. Dimension: A category of information. Ex. the time dimension. Attribute: A unique level within a dimension. Ex. Month is an attribute in the Time Dimension. Hierarchy: The specification of levels that represents relationship between different attributes within a dimension. Ex. one possible hierarchy in the Time dimension is Year → Quarter → Month → Day. Fact Table: A fact table is a table that contains the measures of interest. Ex. Sales Amount is a measure.
• Star Schema – A single object (the fact table) sits in the middle and is radically connected to other surrounding objects (dimension lookup tables) like a star. Each dimension is represented as a single table. The primary key in each dimension table is related to a foreign key in the fact table. • Snowflake Schema – An extension of the star schema, where each point of the star explodes into more points. In a star schema, each dimension is represented by a single dimensional table, whereas in a snowflake schema, that dimensional table is normalized into multiple lookup tables, each representing a level in the dimensional hierarchy.
After the team and tools are finalized, the process follows below steps in waterfall: a)Requirement Gathering b)Physical Environment Setup c)Data Modeling d)ETL e)OLAP Cube Design f)Front End Development g)Report Development h)Performance Tuning and Query Optimization i)Data Quality Assurance j)Rolling out to Production k)Production Maintenance l)Incremental Enhancements
Microsoft BI Tools SSIS – This tool in MSBI suite performs any kind of data transfer with flexibility of customized dataflow. Used typically to accomplish ETL processes in Data warehouses. SSRS – provides the variety of reports and the capability of delivering reports in multiple formats. Ability to interact with different kind of data sources SSAS – MS BI Tool for creating a cubes, data mining models from DW. A typical Cube uses DW as data source and build a multidimensional database on top of it.
Power View and Power Pivot – These are self serve BI tools provided by Microsoft. Very low on cost of maintenance and are tightly coupled with Microsoft Excel reporting which makes it easier to interact. Performance Point Servers – It provides rapid creation of PPS reports which could be in any form and at the same time forms can be changed just by right click. Microsoft also provides the Scorecards, dashboards, data mining extensions, SharePoint portals etc. to serve the BI applications.
Data Integration methods
RDBMS – •Copying data from one table to another table(s) •Bulk / Raw Insert operations •Command line utilities for data manipulation •Partitioning data File System – •Copying file(s) from one location to another •Creating flat files, CSVs, XMLs, Excel spreadsheets •Creating directories / sub-directories
Web – •Calling a web service to fetch / trigger data •Accessing ftp file system •Submitting a feedback over internet •Sending an email / SMS message Other – •Generate Auditing / Logging data •Utilizing / maintaining configuration data (static)
T-SQL Best practices
Query to merge data into a table MERGE dbo.myDestinationTable AS dest USING
(
SELECT ProductID , MIN(PurchaseDate) AS MinTrxDate , MAX(PurchaseDate) AS MaxTrxDate FROM dbo.mySourceTable WHERE ProductID IS NOT NULL GROUP BY ProductID ) AS src ON dest.ProductID = src.ProductID WHEN MATCHED THEN UPDATE SET MaxTrxDate = src.MaxTrxDate , MinTrxDate = ISNULL(dest.MinTrxDate, src.MinTrxDate) WHEN NOT MATCHED BY SOURCE THEN DELETE WHEN NOT MATCHED BY TARGET THEN INSERT (ProductID, MinTrxDate, MaxTrxDate) VALUES (src.ProductID, src.MinTrxDate, src.MaxTrxDate); MERGE clause is T-SQL programmers’ favorite as it covers 3 operations in one
Query to get a sequence using CTE ;WITH myTable (id) AS ( SELECT 1 id UNION ALL SELECT id + 1 FROM myTable WHERE id < 10 ) SELECT * FROM myTable
COMMON TABLE EXPRESSIONS (CTEs) are the most popular recursive constructs in T-SQL
Move Rows in a single Query DECLARE @Table1 TABLE (id int, name varchar(50)) INSERT @Table1 VALUES (1, 'Maxwell'), (2, 'Miller'), (3, 'Dhoni') DECLARE @Table2 TABLE (id int, name varchar(50)) DELETE FROM @Table1 OUTPUT deleted.* INTO @Table2 SELECT * FROM @Table1 SELECT * FROM @Table2
OUTPUT clause redirects the intermediate results of UPDATE, DELETE or INSERT into a table specified
Query to generate random password SELECT CHAR(32 + (RAND() * 94)) +CHAR(32 + (RAND() * 94)) +CHAR(32 + (RAND() * 94)) +CHAR(32 + (RAND() * 94)) +CHAR(32 + (RAND() * 94)) +CHAR(32 + (RAND() * 94))
Non-deterministic functions like RAND() gives different result for each evaluation
Funny T-SQL – Try it yourself Aliases behavior is not consistent SELECT 1id, 1.eMail, 1.0eMail, 1eMail Ever seen WHERE clause in SELECT without FROM clause ? SELECT 1 AS id WHERE 1 = 1 IN clause expects column name at its left? Well, not Really! SELECT * FROM myTable WHERE 'searchtext' IN (Col1, Col2, Col3) Two ‘=‘ operators in single assignment in UPDATE? Possible! DECLARE @ID INT = 0 UPDATE mySequenceTable SET @ID = ID = @ID + 1
Thank you!!