DATA WAREHOUSING — Summer 2020

Say TRUE or FALSE with justification. i. Data in the data warehouse is more heterogeneous than homogeneous. ii. Astar schema has one-to-many type of relationship between a dimension and fact table. iii. Record cannot be updated in data warehousing. iv. Data cleaning is large collection of data mostly stored in a computer system. v. Multidimensional OLAP technology is suited for data mart processing. vi. Astop word is a word that occurs so frequently as to be meaningless to the document. vii. Keeping only summary data in an EIS is a good choice.

Explain the challenges associated with naturally evolving architecture.

What do you mean by data granularity? Explain the concerns of granularity in a data warehouse.

Explain the physical design techniques that are especially relevant to the data warehouse environment.

What are profile records? Explain the concept of creating multiple profile records along with appropriate example.

Explain how overflow storage is used and managed in a data warehouse. Also, describe the software support required to make storage overflow possible.

Explain the concepts of variable-length data, lock management, index-only processing and fast restore in the context of data warehouse.

Write a short note on midlevel data model.

What is a multidimensional DBMS? Compare multidimensional DBMS and data warehouse.

What is EIS? State the uses of EIS.

Explain the star and snowflake structures in detail with example.

What do you mean by independent data mart? State its advantages and disadvantages.

Suppose that a data warehouse consists of the four dimensions time, store, customer and rental item, and the two measures count and charge, where charge is the fee that customer has to pay for late . Design Star schema and snowflake schema model

Explain the concept of probabilistic match in brief along with appropriate example.1

Explain the terms “granularity manager” and “ODS”. Explain their importance in the interaction between the web and data warehouse environments.

Explain the issues that may arise out of an effort to match structured and unstructured data based on text.

What is a snapshot? Explain various triggers of a snapshot in brief.