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Microsoft Business Intelligence (MSBI),
Data Warehousing (DW) andData Integration Techniques
Presenter,Valmik Potbhare
http://lnkd.in/bp_3eFm
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May 21, 2014
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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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.
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.
Typical BI Flow
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Data Sources
Users
Data Tools
Data Warehouse
Extraction
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 Reporting2)Forecasting3)Dashboard4)Multidimensional Analysis5)Finding correlation among different factors
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
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.
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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Typical Data warehouse model
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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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Microsoft BI Platform
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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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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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Data Integration methods
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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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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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T-SQL Best practices
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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 MERGE clause is T-SQL programmers’ favorite as it covers 3 operations in oneone
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 COMMON TABLE EXPRESSIONS (CTEs) are the most popular recursive constructs in T-SQLrecursive constructs in T-SQL
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 OUTPUT clause redirects the intermediate results of UPDATE, DELETE or INSERT into a table specifiedUPDATE, DELETE or INSERT into a table specified
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 Non-deterministic functions like RAND() gives different result for each evaluationdifferent result for each evaluation
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