BAILEY LAPOINTEBOB SWAIN

KIMBERLY TREMBLAY

NOVEMBER 30, 2009BUS 345

Business Intelligence

Outline

A brief historyData MartData MiningBusiness Intelligence ToolsSASBusiness UseDepartment Use

History of BI

1958

• BI defined by Hans Peter Luhn

1960s

• Data ware-housing terms defined

1970s

• Beginning of the End-User Computer Era

1980

• Data Mining emerges

•Definition of BI - "the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal."

History of BI

1983

• Teradata intoduces a database management system

1980s

• Concept of Data Warehouse intoduced

1989

• Definition of BI adapting to changes

1990

• Red Brick Systems introduces database management specifically for data warehousing

•BI as an Umbrella Term - "concepts and methods to improve business decision making by using fact-based support systems."

History of BI

1991

• Prism Solutions introduces software for developing a data warehouse

1995

• The Date Warehousing Institute is founded

1996• The Data

Warehouse Tool Kit is published

1997

• Oracle 8 is released

•The Oracle Database is a relational database management system produced and marketed by Oracle Corporation. As of 2009, Oracle remains a major presence in database computing.

Data Mart

“a data mart is a data repository that may derive from a data warehouse or not and

that emphasizes ease of access and usability for a particular designed purpose.”

-SearchSQLServer.com

Data Mining

Customer RelationsHuman Resources

MarketingFraud Detection

Business Intelligence Tools

Many different companiesStatistically driven

Accessible GUIs

Sample SAS Code

Copyright © 2008, SAS Institute Inc.

Business Use

Business intelligence is exclusive to a company. Large or small Various industries

Example: Tom’s of Maine, 150 employees, 90 oral & body care products, 40,000 retail outlets worldwide

Source: http://www.tomsofmaine.com/

Department Use

Sales Department Sales trends Potential customers Profitable employees Cost efficiency Strategy success

Department Use

Marketing Department Demographic customer profile Plan effectiveness Efficient budget use Alignment to customer

Department Use

Research and Development Evaluate Risk Identify opportunities Manage projects Predict pay-off yield

Department Use

Supply Chain Management Relative product cost Inventory level Receivables Payables Network efficiency

Department Use

Benchmarking Standardization Goals

Developing Monitoring

Competition