im01: business intelligence

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ELEMENTARY TO INFORMATION MANAGEMENT Presented by Kelvin Chan IM01: Business Intelligence

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Page 1: IM01: Business Intelligence

ELEMENTARY TO INFORMATION

MANAGEMENT

Presented by Kelvin Chan

IM01: Business Intelligence

Page 2: IM01: Business Intelligence

Introduction

• Business Intelligence (BI) is one of sub-category of Information Management (IM)

• IM is one of the sub-category of Management Information System (MIS)

Page 3: IM01: Business Intelligence

What is Information Management?

• How to collect Daily Transaction Record• How to store Daily Transaction Record• How to manipulate Daily Transaction Record• How to process Data as Information• How to use Information• How to manage Business Glossary• How to relate Daily Transaction Record to other Metrics

and Business Perspectives

Page 4: IM01: Business Intelligence

What are the functions of IM?

• Data Manipulation• Data Analysis• Data Warehousing• Data Cleansing• Data Profiling• Data Modeling

Page 5: IM01: Business Intelligence

What is Business Intelligence?

• How to use the Product of Information Management in a Business and Strategic ways

Data (in technical aspect)

Information (in business aspect)

Page 6: IM01: Business Intelligence

How to do better in Business Intelligence?

• As talked previously, BI is the way you use Data/Information• You must understand well what is your Business (eg.

Business Model and Business Process)• You must have a clear objective of applying BI at your

Organization (eg. Sales Forecast, Performance Management)• You must have a good Data Modeler that well-understand

your Business and transform it into Data Model

Page 7: IM01: Business Intelligence

What is Data Modeling• In technical view, it is the Design of Database, Tables,

Fields, Data Type, Constraints, Optionality, Cardinality and Granularity, etc…

• In business view, we need to come across Business Process Mapping, treat Business Model and Business Process as Input Source, then do a technical step that we call it ETL to implement Data Consolidation and Extraction, and add the business logics to do the Data Transformation and Calculation, lastly feed them into Data Model (known as Data Loading) that we designed it previously for a specific purpose

Page 8: IM01: Business Intelligence

Data Model

• A specific purpose, eg. Departmental need or Generic Purpose

• Sometime, Organizations may have more than one Data Model serving variety of business needs

• One typical exam: Finance Cube, Marketing Cube and Sales Cube may coexists

• In General, Data Warehouse will serve a Generic Purpose within Corporate Level while Data Mart will serve like Cube

Page 9: IM01: Business Intelligence

Business Model to Data Model

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Business Model to Data Model (Cont’d)

Transaction Detail

Store ID Trans. Date Trans Ref. Product No. Product Name Price

3013 2007-11-27 09390 088590917667 IPOD CL 80GB 259.83

3013 2007-11-27 09390 060538892509 PROTECTION PLAN 48.84

3013 2007-11-27 09390 088590918750 IPOD NANO 4GB 154.83

3013 2007-11-27 09390 060538892509 PROTECTION PLAN 48.84

3013 2007-11-27 09390 060958513348 PHILIPS 1GB LK 39.88

3013 2007-11-27 09390 060538892466 PROTECTION PLAN 29.84

Transaction Master

Store ID Trans. Date Trans Ref. Subtotal GST PST Total

3013 2007-11-27 09390 582.06 34.92 46.56 663.54

Page 11: IM01: Business Intelligence

Physical Data Model

PK/FK Shop ID VARCHAR(4) NOT NULLShop Name VARCHAR(50) NOT NULL

Shop DimensionPK/FK Date DATE NOT NULL

Year VARCHAR(4) NOT NULLMonth VARCHAR(2) NOT NULLDay VARCHAR(2) NOT NULL

Date Dimension

PK/FK Product No. VARCHAR(12) NOT NULLProduct Name VARCHAR(50) NOT NULL

Product Dimension

PK/FK Transaction Reference VARCHAR(4) NOT NULLFK Transaction Date DATE NOT NULLFK Store ID VARCHAR(4) NOT NULL

Subtotal NUMBER(18,2) NULLGST NUMBER(18,2) NULLPST NUMBER(18,2) NULLTotal NUMBER(18,2) NULL

Transaction Master FactFK Transaction Date DATE NOT NULLFK Transaction Reference VARCHAR(4) NOT NULLFK Store ID VARCHAR(4) NOT NULLFK Product No. VARCHAR(12) NOT NULL

Price NUMBER(18,2) NULL

Transaction Detail Fact

1..1 1..1

1..1 1..1

1..1

1..n1..n1..n1..n

1..n

Page 12: IM01: Business Intelligence

Popular BI Tools in the MarketBusiness Intelligence Tool VendorIBM Cognos BI IBMMicrostrategy MicrostrategyPentaho BI suite (open source) PentahoJasperSoft (open source) JasperSoftWebFOCUS Information BuildersMicrosoft Business Intelligence (Excel + SSRS + SSAS + MOSS) MicrosoftQlikView QlikTechSAS Enterprise BI Server SAS InstituteTableau Software Tableau SoftwareOracle Enterprise BI Server (OBIEE) OracleOracle Hyperion OracleBusinessObjects Enterprise SAPSAP NetWeaver BI (Powered by HANA) SAP

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Important Considerations When Applying BI• What Data do you have?

– What are the Systems do populate such Data?• How is the Data Quality?

– Is it a Structured-Data?– Are there any Input Validations at your Systems?

• What is your Objectives of using BI?– Is it for Ad-Hoc Analysis?– Is it a Departmental Decision?– Is it just a Reporting Engine?

• What is your Budget for this BI Project?– Budget Plan should include both Project Implementation and on-

going Cost• What is your Target Scope of this BI Project?• When is your Expected Completion Date?• Will you train up your own BI Team?

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