MD240 - MIS

Oct. 4, 2005

Databases & the Data AssetHarrah’s & Allstate Cases

Topics Covered

• Data & Information– Data vs. information

• Architecture basics– Data Warehouses & Data Marts– Transactional vs. query systems

• Leveraging Data– Harrah’s– Allstate

Data, Information, & Knowledge

• Data - raw facts, figures, and details.

• Information - organized, meaningful, and useful interpretation of data. Has a context, answers a question.

• Knowledge - an awareness and understanding of a set of information and how that information can be put to best use.

• Many firms are data rich and info poor: victims of an old or poorly planned architecture

Examples of Data, Information, & Knowledge

Data: raw, no context 900,000 1,150,000 1,200,000 1,100,000

Information: meaningful, has contextQuarter 1 Quarter 2

Post 900,000 1,150,000 Kellogg's 1,200,000 1,100,000

Post lowered its prices after the first quarter.Price change has caused Post sales to rise at the expense of Kellogg’s

Knowledge: information above & other information creates an awareness of impact

Clients, Servers, DBMS, and Databases

• Database– a collection of related data. Usually organized according to topics: e.g. customer

info, products, transactions

• Database Management System (DBMS)– a program for creating & managing databases; ex. Oracle, MS-Access, MS SQL

Server, IBM DB2, mySQL• SQL - Structured Query Language

– Most popular relational database standard. Includes a language for creating & manipulating data.

DBMS - the program. Manages interaction with databases.

database - the collection of data.Created and defined to meet theneeds of the organization.

Client - makes requests of the server

request

response

Server - responds to client requests

A Simple Database

• File/Table– Customers

• Field/Column– 5 shown: CUSTID, FIRST, LAST, CITY, STATE

• Record/Row– 5 shown: one for each customer

CUSTID FIRST LAST CITY STATE …2001 John Gallaugher Newton MA …2002 Abby Johnson Boston MA …2003 Warren Buffet Omaha NE …2004 Peter Lynch Marblehead MA …2005 Charles Schwab San Francisco CA …

CUSTID FIRST LAST CITY STATE2001 John Gallaugher Newton MA2002 Abby Johnson Boston MA2003 Warren Buffet Omaha NE2004 Peter Lynch Marblehead MA2005 Charles Schwab San Francisco CA

Now With More Data

One

Many

BROKID FIRST LAST …B001 Ivan Boesky …B002 Dennis Levine …B003 Michael Milken …

CUSTID BROKID BUY/SELLSTOCK SHARES PRICE DATE TIME2001 B003 Buy MSFT 1000 90 1/4 12/24/2003 12:01 PM2001 B001 Buy INTC 2400 80 1/8 7/3/2004 10:51 AM2001 B003 Sell IBM 3000 114 3/8 7/1/2004 9:03 AM2002 B001 Sell IBM 3000 110 1/8 6/30/2005 4:53 PM2002 B003 Sell INTC 2000 94 7/8 8/30/2005 3:15 PM

… … … … … … … …

One

Many

Customer Table

Transaction Table

Broker Table

Meta-Data

• Data that describes the characteristics of stored data• Enterprise Data Model

– consistent, cross-functional, shareable meta-data model– standardization increases flexibility & use (data to info)– facilitates the creation of data warehouses

Col. Name Length Type …CUSTID 4 Char …FIRST 10 Char …LAST 15 Char …CITY 15 Char …STATE 2 Char …… … … …

Col. Name Length Type …CUSTID 4 Char …BROKID 4 CharBUY/SELL 1 Bool …STOCK 4 Char …SHARES 8 Num …PRICE 6.2 Money …… … … …

Col. Name Length Type …BROKID 4 CharFIRST 10 Char …LAST 15 Char …… … … …

1

1

mm

Customer Table Transaction Table

Broker Table

Warehouses & Marts

• Data Warehouse– a database designed to support decision-making in an

organization. It is structured for fast online queries and exploration. Data warehouses may aggregate enormous amounts of data from many different operational systems.

• Data Mart– a database focused on addressing the concerns of a

specific problem or business unit (e.g. Marketing, Engineering). Size doesn’t define data marts, but they tend to be smaller than data warehouses.

Data Warehouses & Data Marts

TPS& other

operational systems

DataWarehouse

Data Mart(Marketing)

Data Mart(Engineering)

3rd party data

= query, mining, etc.

= operational clients

Differing System Demands

network traffic & processor

demands

time

network traffic & processor

demands

time

Managerial Systems

Operational Systems

Query Tools & OLAP• Query Tools

– user-lead discovery. Can return individual records or summaries. Requests are formulated in advance (e.g. “show me all delinquent accounts in the northeast region during Q1”).

• OLAP - Online Analytical Processing– user-lead discovery. Data is explored via “drill down” into the

data by selecting variables to summarize on. Results are usually reported in a cross-tab report or graph (e.g. “show me a tabular breakdown of sales by product, customer, and date”).

OLAPOnlineAnalyticalProcessing

OLAP

• Online Analytical Processing. (example of cross-tab results presented below)

1. business unit

2. product type 3. year

Executive Dashboard – aggregated report presentation of key business indicators

Data Mining

• automated information discovery process, uncovers important patterns in existing data– can use neural networks, regression, decision

trees, or other approaches. – Requires ‘clean’, consistent data. Historical data

must reflect the current environment.

• e.g. “What are the characteristics that identify if a customer is likely to default on a loan?”

Insuring Success

Over 5 years:• Revenues up 26%

to $33.9 billion • Profits up 180% to

$3.1 billion • Stock up 187%

– Insurance stocks up only 31%