1. using data strategically
adopted some materials from David Schuff

2. why data?

3. Key bank saved $500,000 by
improving their direct mailing
using data mining and data
warehouse in their Home Equity
Loan program.

4. Airline industry can forecast at
the seat level for each flight to
perform “yield” management.

5. learn insights such as “30+ male
customers buy 6-pack beer and
disposable diaper at the same
time around 2-4 am”

6. Progressive Insurance can offer
usage-based insurance plan using
their database

7. ESS – Executive
Support Systems
DSS – Decision Support
Systems
MIS – Management
Information Systems
TPS – Transaction
Processing Systems
Strategic
Management
Tactical
Management
Business
Operations

8. data becomes the basis of these
different levels of decision making

9. two different types of data-
usages:
transactional
vs.
informational

10. report (using query)
vs.
decision-making (mining)

11. What is a database?
!! Structured collection of data items
!! Types of Database Management Systems
(DBMS)
"! Hierarchical
"! Network
"! Relational
•! The one most often seen
•! Access, MS SQL Server, Oracle, DB2

12. What is a Relational Database?
!! A set of two or more tables related to each other
through key fields
!! Key field
"! A field on which a table can be sorted (indexed)
!! Primary Key
"! Field which uniquely identifies a record
"! Why have a primary key?
•! There may be many people named John Smith, so how
do you tell them apart?
•! Use something which is unique, like a social security
number
•! Social security number is a common key field

13. Data-Driven DSS
(a.k.a. Business Intelligence)
!! Also known as Data Mining and OLAP
(Online Analytical Processing)
!! Finding non-obvious patterns in data
!! Data Mining generally implies using statistical
techniques
"! correlation analysis
"! clustering to find patterns and relationships
in large databases

14. Operational and
informational data stores

15. !! Relational databases are optimized for efficiency
in data storage
"! OLTP – Online transaction processing
!! Dimensional databases are optimized for
efficiency in data retrieval
"! OLAP – Online analytical processing
"! MOLAP – Multidimensional OLAP
•! Stored in cubes that can be easily retrieved and
aggregated
!! ROLAP – Relational OLAP
"! “Fakes” MOLAP-style aggregation using a relational
database

16. Data warehouse
implementation: The data cube
A data cube
stores its data
in a single
table.
That table is
organized
along
dimensions.
This cube has
three
dimensions:
store,
product, and
time.

17. SQL (OLAP) query
•How many light bulbs did we sell in the 1st Qtr
of 2000 in California vs. NewYork?
Data mining query
•How do the buyers of light bulbs in California
and NewYork differ?
•What else do the buyers of light bulbs in
California buy along with light bulbs?
•Which sales regions had anomalous sales in the
1st Qtr of 2000?

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19. !"#$%$"!&'()%*'%+&*",'(*-$"
Divisional DB
Corporate Data
Warehouse
Cleaning
Collecting
ERP system
Data Mining
OLAP
Data Visualization

20. key issues:
• reliability
• scalability
• security
• speed
• data integrity
• availability

21. data may be boring, but the most
critical element in IT architecture