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Explaining the role of metadata in data acquisition process
Question 1) You are a vice president of marketing for a nation-wide appliance manufacturer with three production plants. Explain different ways you would tend to analyze your sales. What are the business dimensions for your analysis?
Question 2) You are a manager for data warehouse project at the retail chain with stores all across the country and users in every store. How would you ensure that all the details essential to decide on DBMS are gathered during the requirements phase? Write a memo to the Senior Analyst directly responsible to coordinate the requirements definition phase.
Question 3) You have recently been promoted to administrator for the data warehouse of a nationwide automobile insurance company. You are asked to prepare a checklist for selecting a proper vendor tool to help you with the data warehouse administration. Make the list of the functions in the management and control component of your data warehouse architecture. Use this list to derive tool-selection checklist.
Question 4) As a data acquisition specialist, what types of metadata can help you? Select one of the data acquisition processes and explain the role of metadata in that process.
Question 5) What is a factless fact table? Design a simple STAR schema with a factless fact table to track patients in a hospital by diagnostic procedures and time.
Design a dimensional model for analysing Purchases for Adventure Works Cycles and implement it as cubes using SQL Server Analysis Services. The AdventureWorks OLTP sample database is the data source for you BI analysis.
Design a Database schema
Create an entity-relationship diagram and design accompanying table layout using sound relational modeling practices and concepts.
Implement a database of courses and students for a school.
Energy in the home, personal energy use and home energy efficiency and Efficient use of ‘waste' heat and renewable heat sources
Design relation schemas for the entire database.
Prepare the relational schema for database
Data Modeling and Normalization
Use Cases Perform a requirements analysis for the Case Study
Knowledge and Data Warehousing
Identify and explain the differences between a stack and a queue data structure
Practice on topic of Normalization
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