Question 1

What is an automated workflow called in Zapier?

Accepted Answer

In Zapier, an automated workflow is called a Zap. Each Zap consists of a trigger (the initiating event) and one or more actions (tasks performed automatically). Zaps connect different applications together without writing code, making them a central tool in no-code automation.

Question 2

Which chart type is best suited for comparing values across different categories?

Accepted Answer

The bar chart is the most effective chart for comparing values across distinct categories. The human eye is very efficient at comparing lengths aligned on a common axis, making the reading intuitive. Bars can be vertical or horizontal depending on the number of categories and label length.

Question 3

What is the main Pandas data structure for storing tabular data?

Accepted Answer

The DataFrame is the core Pandas data structure. It represents a two-dimensional table with rows and columns, similar to a spreadsheet or SQL table. Each column is a Series, and each row has an index. The DataFrame enables efficient manipulation of structured data through its many built-in methods.

Question 4

Which cell reference designates the cell located in column B, row 5?

Accepted Answer

In Google Sheets, cell references always use the column letter followed by the row number. Column B with row 5 therefore gives B5. This notation allows for precise identification of each cell in a spreadsheet.

Question 5

Which chart type is most suitable for displaying monthly revenue evolution over a year in a Google Sheets dashboard?

Accepted Answer

A line chart is the optimal choice for visualizing continuous time-series evolution. It highlights trends, peaks, and troughs over a given period. Bar charts are better suited for categorical comparisons, pie charts for proportions of a whole, and scatter plots for correlations between two variables.

Question 6

What is a subquery in SQL?

Accepted Answer

A subquery is a query nested inside another SQL query. It can appear in SELECT, FROM, WHERE, or HAVING clauses. The subquery executes first and its result is used by the outer query. This mechanism allows breaking down complex problems into successive logical steps.

Question 7

What is a window function in SQL?

Accepted Answer

A window function performs a calculation across a set of rows related to the current row, without collapsing the results into a single output row. Unlike GROUP BY which reduces the number of rows, a window function preserves all rows in the result while adding a computed column. The OVER() clause defines the window over which the calculation is performed.

Question 8

In a cohort analysis, what is the main role of the first touch date?

Accepted Answer

The first touch date allows grouping users into cohorts based on when they first interacted with the product. This temporal segmentation is essential for comparing the behavior of user groups acquired at different periods and identifying trends or performance changes over time.

Question 9

What is the difference between a macro and a model in dbt?

Accepted Answer

A macro is a reusable Jinja code block that generates SQL dynamically, while a model is a SQL file that produces a table or view in the data warehouse. Macros help factorize repetitive code and create custom functions, whereas models define the structure of transformed data.

Question 10

What is the fundamental difference between a measure and a calculated column in DAX?

Accepted Answer

A measure is calculated dynamically with each user interaction (filter, slicer) in the current visualization context, while a calculated column is evaluated once during data load and stored in memory within the table. Measures are optimal for aggregations and KPIs that change based on context, calculated columns for fixed attributes requiring sorting or grouping.

Data Analytics interview questions

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Google Sheets - Fundamentals

Google Sheets - Advanced Formulas

SQL - Fundamentals

SQL - Aggregations and Grouping

SQL - Joins

BigQuery - Fundamentals

Data Cleaning

KPIs and Business Metrics

Descriptive Statistics

Zapier and No-Code Automation

Data Visualization Principles

Python & Pandas - Fundamentals

Google Sheets - Automated Dashboards

SQL - Subqueries and CTEs

SQL - Window Functions

BigQuery - Advanced Features

Data Modeling

Funnel and Conversion Analysis

Cohort and Retention Analysis

Google Tag Manager and Tracking

APIs and Webhooks

dbt - Fundamentals

AB Testing and Applied Statistics

Looker Studio (Google Data Studio)

Power BI - Fundamentals

SQL - Advanced Analytical Queries

dbt - Advanced Features

Power BI - DAX and Advanced Dashboards

Python Analytics - Advanced Analysis and ML

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