Business Intelligence Concepts

RAJASHMITA KARrajashmita.kar@tcs.com

April 13, 2011

AGENDA

Dec 16, 2013

What is BI??

BI Lifecycle

Chalenges of Building BI Data Warehouse Concepts Key Performance Indicator

Normalization and its type

Data Cleansing Slowly Changing Dimension

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What is BI??

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April 13, 2011

The term Business Intelligence (BI) represents the tools and systems that play a key role in the strategic planning process of the corporation.

These systems allow a company to gather, store, access and analyze corporate data to aid in decision-making.

It is an environment in which business users receive information that is reliable, secure, consistent, understandable, easily manipulated and timely...facilitating more informed decision making.

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April 13, 2011

BI LIFECYCLE

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April 13, 2011October 30, 2012

Prod

Mkt

HR

Fin

Acctg

Data Sources

Transac tion D ata

IBM

IMS

VSAM

Oracle

Sybase

ETL Software Data Stores Data AnalysisTools and Applications

Users

Other In ternal D ata

ERP SAP

Clickstream Informix

W eb D ata

External Data

Demographic Harte-Hanks

STAG ING

AREA

OPERAT IONAL

DATA

STORE

Ascential

Extract

Sagent

SAS

Clean/ScrubTrans formFi rst logic

Load

Informatica

Data Mart sTeradataIBM

Data Warehouse

Meta Data

Finance

Marketing

Sales

Essbase

Microsoft

A NA L YS TS

M AN A GER S

EX EC U TIV ES

OPER A TIO NA LPER SO NN EL

C US TOM ER S/SU PPLIE RS

SQL

Cognos

SAS

Queri es,Reporting,DSS/EIS, Data Mining

Micro Strat egy

Siebel

BusinessObjects

WebBrowser

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Challenges of Building BISolution

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Data exists in multiple placesData is not formatted to support complex analysisDifferent kinds of workers have different data needsWhat data should be examined and in what detailHow will users interact with that data

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Data WareHouse

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Components of Data Warehouse

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Cubes Measures Key Performance Indicator Dimensions ---Attributes ---Hierarchy

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DATA MODELLING

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DATA MODELING

• process that produces abstract data models for one or more database components of the data warehouse

Types of Data Modeling– Conceptual Data Model– Logical Data Model– Physical Data Model

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DIMENSIONAL MODELLING

• Fact Table• Dimension Table

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STAR SCHEMA AND SNOW FLAKES SCHEMA

STAR SCHEMA SNOW FLAKES SCHEMA

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KEY PERFORMANCE INDICATOR (KPI)

• A set of quantifiable measures that a company or industry uses to gauge or compare performance in terms of meeting their strategic and operational goals.

• KPIs vary between companies and industries, depending on their priorities or performance criteria

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NORMALIZATION

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NORMALIZATIONDatabase normalization is the process of removing

redundant data from your tables in to improve storage efficiency, data integrity, and scalability.

Normalization Forms:

• First Normal Form(1NF)• Second Normal Form(2NF)• Third Normal Form(3NF)• Boyce-Codd Normal Form(BCNF)

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3NF

Third normal form (3NF) requires that there are no functional dependencies of non-key attributes on something other than a candidate key. A table is in 3NF if all of the non-primary key attributes are mutually independent

There should not be transitive dependencies

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If I know # of Pages, can I find out Author's Name? No. Can I find out Author's pseudonym? No. If I know Author's Name, can I find out # of Pages? No. Can I find out Author's pseudonym YES.

Therefore, Author's pseudonym is functionally dependent upon Author's Name, not the PK for its existence. It has to go.  

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BCNFClient Interview

-FD1 clientNo, interviewDate � interviewTime, staffNo, roomNo (Primary Key)-FD2 staffNo, interviewDate, interviewTime � clientNo (Candidate key)-FD3 roomNo, interviewDate, interviewTime � clientNo, staffNo (Candidate key)-FD4 staffNo, interviewDate � roomNo (not a candidate key)-As a consequece the ClientInterview relation may suffer from update anomalies.-For example, two tuples have to be updated if the roomNo need be changed for staffNo SG5 on the 13-May-02.

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To transform the ClientInterview relation to BCNF, we must remove the violating

functional dependency by creating two new relations called

Interview and StaffRoom as shown below,

Interview (clientNo, interviewDate, interviewTime, staffNo),

StaffRoom(staffNo, interviewDate, roomNo)

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DATA CLEANSING

HOWWHAT

WHEN

WHY

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SLOWLY CHANGING DIMENSION(SCD)

• Dimensions that change over time are called SCD• Example: Product Price, Customer Address etc

• SCD Types:– Type I SCD– Type II SCD– Type III SCD– Type 4 SCD

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SCD (IMPLEMENTATION)DIMENSIONS

CATEGORYBRANDMODELSTOREVENDOR

FACTSINVENTORY_TRANSACTION_FILE

GOODS_RECEIVING

SCD IMPLEMENTED ON DIMENSION TABLES ONLY AND NOT ON FACT TABLES

CATEGORY (SCD I)

BRAND (SCD I)

MODEL (SCD II by DATE)

STORE (SCD II by FLAG)

VENDOR (SCD I)

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April 13, 2011

THANK YOU

Dec 16, 2013