BeeHyv Senior Data Analyst Interview Questions, Process, and Tips

Q1. Power BI optimization techniques.
Ans. 
Power BI optimization techniques involve data model optimization, query optimization, and report design best practices.
• Optimize data model by removing unnecessary columns and relationships

• Use query folding to push data transformation tasks to the data source

• Avoid using calculated columns and instead use measures for calculations

• Limit the use of visuals that require high computational resources

• Use aggregations and compo
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Q1. How to handle large datasets.
Ans. 
Handling large datasets involves optimizing storage, processing, and analysis techniques.
• Use distributed computing frameworks like Hadoop or Spark to process data in parallel.

• Utilize data compression techniques to reduce storage requirements.

• Implement indexing and partitioning strategies to improve query performance.

• Consider using cloud-based storage and computing resources for scalability.

• Use sampling techniques to wo
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Q2. How to use parameters.
Ans. 
Parameters are variables that can be passed into a function or procedure to customize its behavior.
• Parameters are defined when creating a function or procedure.

• They can be used to pass values into the function or procedure.

• Parameters can be required or optional, with default values specified.

• They help make functions more flexible and reusable.

• Example: def calculate_area(length, width):
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Q3. Row lovel Security.
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Q1. SQL interview. How to get the rolling sum of sales.
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Q2. Get current month and previous month sales in same row.
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Q1. Gateway. Refresh, Incremental Refresh and other service related.
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Q2. Write DAX to calculate some values.
Ans. 
Calculating values using DAX in Power BI
• Use SUMX function to calculate sum of values in a column

• Use CALCULATE function to apply filters and conditions to calculations

• Use DAX measures to create reusable calculations

• Example: Calculate total sales for a specific product category
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Q3. Create data model and visualizations.
Ans. 
Creating data model and visualizations involves structuring data and presenting it visually.
• Identify the key variables and relationships in the data

• Design a data model that represents the data structure

• Select appropriate visualization tools and techniques

• Create visualizations such as charts, graphs, and dashboards

• Ensure the visualizations effectively communicate insights from the data
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Was asked questions on Permutations and Combinations like the once you see in Math Olympiads.

Q1. Asked about past project experience.
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