The presentation used to get the conceptual understanding of Business Intelligence and Data warehousing applications. This also gives a basic knowledge about Microsoft's offerings on Business Intelligence space. Lastly but not least, it also contains some useful and uncommon SQL server programming best practices.

1. www.synerzip.com
Microsoft Business Intelligence
(MSBI),
Data Warehousing (DW) and
Data Integration Techniques
Presenter,
Valmik Potbhare
http://lnkd.in/bp_3eFm
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May 21, 2014

2. Agenda
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 What is BI?
 What is Data Warehousing?
 Microsoft platform for BI applications
 Data integration methods
 T-SQL examples on data integration
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3. What is BI?
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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.

4. BI Case
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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.

5. Typical BI Flow
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Data Sources
Users
Data Tools
Data Warehouse
Extraction

6. Why BI?
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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

7. What is Data warehousing?
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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

8. Dimensional Data Model
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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.

9. Data warehouse designs
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• 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.
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10. Typical Data warehouse model
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11. Data warehouse implementation
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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
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12. Microsoft BI Platform
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13. Microsoft BI Tools
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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.
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14. MSBI Tools
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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.
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15. Confidential
Data Integration
methods
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16. Different ways of integration
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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
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17. Different ways of integration
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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)
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18. Confidential
T-SQL
Best practices
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19. Query to merge data into a table
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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 oneMERGE clause is T-SQL programmers’ favorite as it covers 3 operations in one

20. Query to get a sequence using CTE
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;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 recursiveCOMMON TABLE EXPRESSIONS (CTEs) are the most popular recursive
constructs in T-SQLconstructs in T-SQL

21. Move Rows in a single Query
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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,OUTPUT clause redirects the intermediate results of UPDATE,
DELETE or INSERT into a table specifiedDELETE or INSERT into a table specified

22. Query to generate random password
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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 differentNon-deterministic functions like RAND() gives different
result for each evaluationresult for each evaluation

23. Funny T-SQL – Try it yourself 
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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

24. Confidential 24
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