Page 109 - DCAP603_DATAWARE_HOUSING_AND_DATAMINING

Unit 5: Data Warehouse Research – Issues and Research

Fill in blanks: notes
3. The source systems for a ..................... are typically transaction processing applications.

4. The data is extracted completely from the source system known as .....................
5. ..................... is based on a comparison of the data loaded into business intelligence and the
application data in the source system.
6. Data reconciliation for DataSources allows you to check the ..................... of the loaded
data.
7. The ..................... of the data and the processes of the data warehouse is heavily dependent
on the design process.
8. ..................... is related to the accessibility dimension, since the sooner the queries are
answered.
9. ..................... defined quality as the loss imparted to society from the time a product is
shipped.
10. Three perspective of data warehouse metadata are logical, physical and .....................

5.12 review Questions

1. What do you mean by data extraction?

2. Describe logical extraction methods of data.
3. Distinguish between online and offline extraction.
4. Explain modeling aspects of data reconciliation.
5. What do you mean by data aggregation?

6. Describe basic principles of query optimization.
7. Explain various strategies of query optimization.
8. “As a decision support information system, a data warehouse must provide high level
quality of data and quality of service”. Explain

9. Write a short note on data quality research.
10. What are the three perspectives of data warehouse metadata?

answers: self assessment

1. (a) 2. (c)
3. data warehouse 4. Full extraction
5. Data reconciliation 6. integrity
7. interpretability 8. Query optimization

9. Taguchi 10. Conceptual

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