1. A company’s sales data has three dimensions: Time, Product, and Geography. If the sales data for the first quarter of this year is stored in a star schema, how would you optimize the query to retrieve the top three products sold in each region during that period?
2. You have a data Mart that aggregates daily sales data. If you notice the daily reports are consistently underreporting the total sales by around 10%, what steps will you take to identify and resolve the issue?
3. Given a fact table that records transactions and a dimension table for customers, design a method to analyze customer buying patterns over time. What key metrics would you track and why?
4. Imagine you have a data warehouse with a large amount of historical data, but due to evolving business needs, a new data model is required that supports new analysis. How would you approach migrating the existing data to the new model without losing integrity?
5. You are tasked with creating a report for a business unit that needs insights on customer retention. Describe the steps you would take to extract the necessary data and what analytical methods you would apply to measure retention rates.
6. A retail company needs to analyze their seasonal sales trends. If they have multiple sources of data (sales transactions, inventory data, and promotional data), explain how you would integrate these different data sets for effective analysis using a data warehouse.
7. A query from your data warehouse is taking significantly longer than expected to execute. What strategies would you employ to diagnose performance issues and improve the speed of the query?
8. You are given a dataset containing hundreds of thousands of rows with customer transaction data, and you need to identify outliers in the spending patterns. What statistical methods or algorithms would you use to detect these outliers?
9. You're implementing a slowly changing dimension (SCD) for customer demographics in your data warehouse. Explain the type of SCD you would choose, and what considerations would drive your decision?
10. Design a data warehouse schema for a fictional online streaming service. Include at least five tables and explain how they interact to answer common business questions related to user engagement.
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