BCG Data Analyst Interview Questions and Answers

Q1. Power BI Difference between ALL() and ALLSELECTED()
Ans. 
ALL() ignores all filters in the query context, while ALLSELECTED() ignores only filters on columns in the visual.
• ALL() removes all filters from the specified column or table.

• ALLSELECTED() removes filters from the specified column or table, but keeps filters on other columns in the visual.

• Example: ALL('Table') would remove all filters on the 'Table' in the query context.

• Example: ALLSELECTED('Column') would remove filte...read more
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Q2. Excel Difference between COUNT() and COUNTA()
Ans. 
COUNT() counts only numeric values, while COUNTA() counts all non-empty cells.
• COUNT() counts only cells with numerical values.

• COUNTA() counts all non-empty cells, including text and errors.

• Example: COUNT(A1:A5) will count only cells with numbers, while COUNTA(A1:A5) will count all non-empty cells.
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Q1. Resume based questions like explain the projects that you have done.
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Q2. Sample dataset questions
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Q1. What makes you believe you are a good fit for this position?
Ans. 
I have a strong background in data analysis, with experience in utilizing various analytical tools and techniques to derive insights from data.
• I have a degree in Statistics and have completed multiple data analysis projects during my academic career.

• I am proficient in using programming languages such as Python and R for data analysis.

• I have experience working with SQL databases and extracting data for analysis.

• I have s...read more
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Q1. What are SQL window functions and how are they used in database queries?
Ans. 
SQL window functions are used to perform calculations across a set of table rows related to the current row.
• Window functions operate on a set of rows related to the current row, known as a window.

• They can be used to calculate running totals, ranks, averages, and more.

• Common window functions include ROW_NUMBER(), RANK(), DENSE_RANK(), SUM(), AVG(), and LEAD().
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Basic quant questions with some questions on ML. 2 python questions based on data processing.

Q1. Difference between list and set
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Q2. Difference between concat and merge
Ans. 
Concat is used to combine data along a particular axis, while merge is used to combine data based on a common key.
• Concatenation is done along an axis (rows or columns) in pandas, while merging is done based on common columns or indices.

• Concatenation is a simple operation that just appends data, while merging involves combining data based on a key.

• Concatenation can be done even if the data does not have common columns, ...read more
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4 rounds of coding ml questions