Data Analyst Interview Questions with Answers

Data Analyst Interview Questions with Answers

How do you perform joins in Power BI using relationships?

In Power BI, joins are handled through relationships between tables instead of traditional SQL joins. You can create relationships using the Model View, where you define one-to-one, one-to-many, or many-to-many relationships. Power BI automatically determines the best relationship based on column values, but you can modify the cardinality and cross-filter direction to control how data is connected across tables.

What are some common aggregate functions in Excel?

Aggregate functions summarize data in Excel. Common ones include:
SUM: Adds values in a range.
AVERAGE: Calculates the mean.
COUNT: Counts the number of non-empty cells.
MAX/MIN: Finds the highest and lowest values.
MEDIAN: Returns the middle value of a dataset.
STDEV: Measures data variation (Standard Deviation).
These functions are commonly used in financial analysis, data validation, and reporting.

What are DAX functions in Power BI, and why are they important?

DAX (Data Analysis Expressions) functions help create custom calculations and measures in Power BI. They are important because they allow users to perform dynamic aggregations, conditional calculations, and time-based analysis. Key categories include:
Aggregation Functions: SUM, AVERAGE, COUNT
Filter Functions: FILTER, CALCULATE
Time Intelligence Functions: DATEADD, SAMEPERIODLASTYEAR
Logical Functions: IF, SWITCH
DAX enables advanced reporting and helps build meaningful insights from raw data.

What is data normalization, and why is it important?

Data normalization is the process of organizing data in a database to reduce redundancy and improve data integrity. It ensures efficient storage and retrieval by dividing large tables into smaller, related tables and using foreign keys to maintain relationships.

Benefits of normalization include:

Eliminates duplicate data
Improves consistency and accuracy
Enhances database performance
Reduces data anomalies

Normalization is crucial in relational databases to maintain a clean and scalable data structure.

What are some common data visualization best practices?

Effective data visualization helps communicate insights clearly. Best practices include:

Choose the right chart (e.g., bar charts for comparisons, line charts for trends).
Keep it simple (avoid unnecessary elements like 3D effects).
Use colors wisely (highlight key insights without overloading with colors).
Ensure data accuracy (labels, scales, and values must be correct).
Use interactive elements (filters, drill-downs in Power BI/Tableau).
Provide context (titles, legends, and annotations to explain findings).

Well-designed visualizations improve decision-making and help stakeholders understand data easily.