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environment. - The data transformation function encompasses data conversion, cleansing, consolidation, and integration. Implement the transformation function using a combination of specialized tools and in-house developed software. - The data loading function relates to the initial load, regular periodic incremental loads, and full refreshes from time to time. Four methods to apply data are: load, append, destructive merge, and constructive merge. - Tools for ETL functions fall into three broad functional categories: data transformation engines, data capture through replication, and code generators. - Enterprise Information Integration (EII) and Enterprise Application Integration (EAI) are some other approaches to data integration. REVIEW QUESTIONS 1. Give three reasons why you think ETL functions are most challenging in a dats warehouse environment. 2. Name any five types of activities that are part of the ETL process. Which of these are time consuming? 3. The tremendous diversity of the source systems is the primary reason for their complexity. Do you agree? If so, explain briefly why. 4. What are the two general categories of data stored in source operational systems? Give two examples for each. 5. Name five types of the major transformation tasks. Give an example for each. 6. Describe briefly the entity identification problem in data integration and consolidation. How do you resolve this problem? 7. What is key restructuring? Explain why it is needed. 8. Define initial load, incremental load, and full refresh. 9. Explain the difference between destructive merge and constructive merge for applyity data to the data warehouse repository. When do you use these modes? 10. When is a full data refresh preferable to an incremental load? Can you think of an example