BI Analyst Interview Questions and Answers

I will communicate the technical advantage to a business user by using simple and relatable examples.

• Use non-technical language to explain the advantage

• Relate the advantage to real-life scenarios or business goals

• Provide concrete examples and case studies

• Highlight the impact and benefits of the technical advantage

To show aggregation on whole data row by row in SQL, you can use the OVER() function with appropriate window specification.

• Use the OVER() function to perform aggregation on the entire data set

• Specify the window specification to define the scope of aggregation

• Add the aggregated result as a new column in the existing table

• Example: SELECT *, SUM(sales) OVER() AS total_sales FROM table_name

ALL function in DAX returns all the rows in a table, or all the values in a column, ignoring any filters that might have been applied.

• ALL function can be used to remove filters from a table or column.

• It can also be used to remove filters from a specific column in a table.

• ALL function can be combined with other functions like CALCULATE to perform complex calculations.

• Example: CALCULATE(SUM(Sales[Amount]), ALL(Sales[Product])) will return the total sales amount for all products...read more

Functions return a single value while stored procedures execute a set of SQL statements.

• Functions are used to perform calculations and return a single value while stored procedures are used to execute a set of SQL statements.

• Functions can be used in SELECT, WHERE, and HAVING clauses while stored procedures cannot.

• Functions can be called from within stored procedures while stored procedures cannot be called from within functions.

• Functions cannot modify the database while store...read more

I am highly proficient in SQL with extensive experience in writing complex queries and optimizing database performance.

• Extensive experience writing complex SQL queries

• Optimizing database performance through efficient SQL coding

• Familiarity with advanced SQL concepts such as subqueries, joins, and indexing

Python has various data types like int, float, str, list, tuple, dict, set, bool, etc.

• Common data types in Python include int (integer), float (floating point number), str (string), list (ordered collection), tuple (immutable collection), dict (key-value pairs), set (unordered collection), bool (boolean)

• Data types can be checked using the type() function

• Examples: int - 5, float - 3.14, str - 'hello', list - [1, 2, 3], tuple - (1, 2, 3), dict - {'key': 'value'}, set - {1, 2, 3...read more

Power Query is a data connection technology that enables you to discover, connect, combine, and refine data across a wide variety of sources.

• Power Query is a data connection technology in Power BI used for data transformation and manipulation.

• It allows users to import data from various sources, clean and transform the data, and load it into the Power BI data model.

• Power Query uses a graphical interface to apply transformations to data, such as filtering, sorting, and merging....read more