MD240 - MIS Oct. 4, 2005 Databases & the Data Asset Harrah’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 Information: meaningful, has context 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 the needs 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

Now With More Data One Many 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 1 1 m m 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 Data Warehouse 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”).

OLAP Online Analytical Processing

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%