MSS may have data problems, such as incorrect data, warehouse. They are a less expensive solution that can nontimelv data, poorly measured and indexed data, too

9 MSS may have data problems, such as incorrect data, warehouse. They are a less expensive solution that can nontimelv data, poorly measured and indexed data, too

be replaced by or can supplement a data warehouse. many data, or no data.

• Data marts can be independent of or dependent on a • Commercial online databases, such as CompuServe and

data warehouse.

Dow Jones Information Service, can be major sources of • Data multidimensionality enables people to view data MSS/BI data.

quickly in different dimensions, even if the data are in • The Internet has become a major external data source

different files and databases.

• Business intelligence is moving toward real-time • Intranets are providing internal data for MSS/BI.

for MSS/BI.

capabilities.

• Most major databases have Web links to enable direct • Visualization is an important business intelligence query via WEB browsers on client workstations.

capability.

• Data are usually organized in relational, hierarchical, or • Business intelligence methods include OLAP and data network architectures. For many MSS/BI/BA, the

mining.

relational database type is preferable. • Online analytical processing (OLAP) is a set of tools • Structured query language (SQL) is a standard means

for timely data analysis. It is extremely important in of access for querying relational databases.

MSS/BI/BA applications.

• Multimedia databases have become increasingly more • Data mining is the discovery of knowledge in databases. important for decision-making applications.

It is often done on data in data warehouses. • Object-oriented databases are easy to use and can be

• Data mining can be hypothesis-driven or discovery- accessed very quickly. They are especially useful in

driven.

distributed MSS and complex DSS. • The Web continues to impact dramatically on how • One of the most critical objectives is to make databases

database management systems are developed and intelligent so that users can find information quickly by

operate.

themselves.

• KEY W O R D S • business analytics

• object-oriented database • business intelligence

• dependent data mart

management system (OODBMS) • client/server architecture

• development technology

• online analytical processing • content-management system

• discovery-driven data mining

• document management systems

(OLAP)

• online (commercial) databases • data

(CMS)

(DMS)

• query tools • data mart

® hypothesis-driven data mining

® relational database • data integrity

• independent data mart

• source systems • data mining

• information

• structured query language (SQL) • data quality (DQ)

• intelligent database

• user participation • data visualization

• Internet

• Web analytics • data warehouse

• knowledge

• Web intelligence • database management systems

• QUESTIONS FOR REVIEW l. Define data, information, and knowledge. Identify 2. Describe the role of the Internet in MSS data man-

P A R T II DECISION SUPPORT SYSTEMS'

3. What is SQL? Why is it important?

14. Define a data warehouse, and list some of its charac-

4. List the major categories of data sources for an

teristics.

MSS/BI.

15. What is the difference between a database and a data

5. Why are data quality and data integrity so important?

warehouse?

6. Describe the benefits of commercial databases.

16. Describe the role that a data warehouse can play in

7. Define object-oriented database management.

MSS. List its benefits.

8. Define document management.

17. Define a data mart and explain why they are impor-

9. Define a star schema.

tant.

10. What are intelligent databases, and why are they so

18. Describe OLAP.

popular?

19. Define data mining and list its major technologies.

20. What is meant by real-time business analytics? to commercial databases?

11. How can an expert system provide a good interface

21. Differentiate data mining, text mining, and Web min-

12. Define data multidimensionality and a multidimen-

ing.

sional database.

22. Distinguish between K D D and data mining.

13. Describe why visualization is so important in business Explain how the Web is impacting business intelli- intelligence.

gence/business analytic methods and technologies.