Answer the following: 1. What is a data warehouse? 2. Which model is typically used for analytical processing in data warehouses? 3. What is the full form of OLAP? 4. What kind of data is stored in a data warehouse—current or historical? 5. Name one OLAP operation used to view data at a higher aggregation level. 6. What is a Data Mart? 7. Which ETL process phase involves cleaning and formatting data?
[7 marks]Explain the structure of a data warehouse, outline the typical process of building it, and discuss granularity with its issues, benefits, and examples.
[7 marks]Explain the role of data models in a data warehouse. Differentiate between mid-level and physical data models. Also, describe the relationship between data modeling and iterative development.
[7 marks]Differentiate between direct and indirect access to data warehouse data with examples. Explain star joins and their significance in querying. Also, define data marts and their role in a data warehouse architecture.
[7 marks]Explain the concept of granularity in a data warehouse. Discuss the basic aspects of granularity and illustrate with examples the different levels of granularity and their implications.
[7 marks]Discuss the importance of indexing and monitoring in a data warehouse environment. Explain different types of indexes used and how data monitoring supports performance and data quality.
[7 marks]Explain the role of context and content in data warehousing. Describe the three types of contextual information and how they are captured and managed in a data warehouse environment.
[7 marks]What is meant by data warehousing across multiple storage media? Explain its significance, challenges, and benefits. Give examples of different storage media used in such architectures. Page 1 of
[2 marks]What is meant by refreshing a data warehouse? Explain different methods of data refresh and the importance of testing in the data warehousing process.
[7 marks]Explain the key OLAP operations: drill-down, roll-up, slice, and dice. Illustrate each with an example and discuss their importance in multidimensional data analysis.
[7 marks]Differentiate between detailed and summarized data in the context of Executive Information Systems (EIS). How does EIS utilize both types of data for effective decision-making? Provide examples.
[7 marks]What is an Executive Information System (EIS)? Discuss its key features, components, and benefits. How does it support strategic decision-making in an organization?
[7 marks]What is meant by migration to the architected environment in data warehousing? Explain the need, process, and challenges involved in migrating legacy systems to a data warehouse architecture.
[7 marks]Compare the Relational Model and the Multi-dimensional Model in the context of data warehousing. Discuss their structures, use cases, and advantages.
[7 marks]What is an Operational Data Store (ODS)? Explain its role, features, and differences from a data warehouse. Provide suitable examples of its use in business operations.
[7 marks]Differentiate between structured and unstructured data. How is textual data handled in data warehousing? Provide examples and techniques used for managing and analyzing textual data.
[7 marks]What is a two-tiered data warehouse architecture? Explain its components, advantages, and limitations. How does it differ from the three-tiered architecture? Page 2 of
[2 marks]