The document discusses information management and business intelligence. It defines information management as collecting, storing, manipulating, processing, and managing business data and glossaries. Business intelligence involves using the products of information management like data warehouses and data marts in strategic business ways. Good business intelligence requires understanding business models and processes, clear objectives, and effective data modeling to transform business needs into usable data models. Popular business intelligence tools are also listed.

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

2. 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)

3. 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

4. What are the functions of IM?
• Data Manipulation
• Data Analysis
• Data Warehousing
• Data Cleansing
• Data Profiling
• Data Modeling

5. What is Business Intelligence?
• How to use the Product of Information
Management in a Business and Strategic ways

6. 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

7. 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

8. 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

9. Business Model to Data Model

10. 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

11. Physical Data Model
Shop Dimension Date Dimension
PK/FK Shop ID VARCHAR(4) NOT NULL PK/FK Date DATE NOT NULL
Shop Name VARCHAR(50) NOT NULL Year VARCHAR(4) NOT NULL
1..1 1..1 Month VARCHAR(2) NOT NULL
Day VARCHAR(2) NOT NULL
1..1
1..1
1..n
1..n
1..n 1..n
Transaction Master Fact Transaction Detail Fact
PK/FK Transaction Reference VARCHAR(4) NOT NULL FK Transaction Date DATE NOT NULL
FK Transaction Date DATE NOT NULL FK Transaction Reference VARCHAR(4) NOT NULL
FK Store ID VARCHAR(4) NOT NULL FK Store ID VARCHAR(4) NOT NULL
Subtotal NUMBER(18,2) NULL FK Product No. VARCHAR(12) NOT NULL
GST NUMBER(18,2) NULL Price NUMBER(18,2) NULL
1..n
PST NUMBER(18,2) NULL
Total NUMBER(18,2) NULL
1..1
Product Dimension
PK/FK Product No. VARCHAR(12) NOT NULL
Product Name VARCHAR(50) NOT NULL

12. Popular BI Tools in the Market
Business Intelligence Tool Vendor
IBM Cognos BI IBM
Microstrategy Microstrategy
Pentaho BI suite (open source) Pentaho
JasperSoft (open source) JasperSoft
WebFOCUS Information Builders
Microsoft Business Intelligence (Excel + SSRS + SSAS + MOSS) Microsoft
QlikView QlikTech
SAS Enterprise BI Server SAS Institute
Tableau Software Tableau Software
Oracle Enterprise BI Server (OBIEE) Oracle
Oracle Hyperion Oracle
BusinessObjects Enterprise SAP
SAP NetWeaver BI (Powered by HANA) SAP

13. 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?