Google Business Analyst Interview Questions + Guide 2025

Over 88% of organizations consider business analysis crucial to their success. Alphabet, Google’s parent company, is among them, with a 34% increase in profit to $26.3 billion and a 15% rise in revenue to $88.27 billion in the third quarter of 2024.

Google, driven by strong performance in its core search business and significant growth in its advertisement segment revolving around data analytics at Google and Google Analytics, employs business analysts in both remote and hybrid roles. However, it’s safe to say you wouldn’t exactly dread a trip to their campus, especially for the lunch and the overall environment.

As a candidate for the business analyst role at Google, you, expectedly, have queries regarding the interview questions and preparation strategies. More than that, you must also be curious to know the responsibilities and impact of your work at Google. So, without further ado, let’s get into it.

A Google business analyst helps Google business processes grow by making smart, data-driven decisions. They analyze big datasets, spot trends, and give insights that help teams improve products like Google Drive, BigQuery, and Google Kubernetes Engine. Your work would help businesses use Google products more efficiently and justify your basic salary band of over $100,000.

The role isn’t just about numbers—it’s about solving problems. Analysts create dashboards, run A/B tests, and track key performance metrics, especially in products like Google Ads and YouTube Analytics. It’s worth mentioning that Android and Google Chrome are among the top Google products that you’ll work on to bring new features to life and improve existing ones through analysis and insights.

They work with teams across Google, from engineers to product managers, to make sure strategies align. One day, you might be analyzing how businesses use Google Workspace; the next, you could be helping improve YouTube algorithms.

To succeed, candidates need strong problem-solving skills, a good grasp of SQL and R, and an understanding of A/B testing and experiment design. Google looks for people who can think critically, communicate insights clearly, and find creative solutions. The interview process includes business case studies, puzzles, and technical questions, so preparation is key.

Career progression for business analysts at Google follows the L3, L4, and L5 structure. At L3, you’ll analyze data, create reports, and support decision-making, while at L4, you take on more responsibility, lead projects, and influence business strategy. At L5, you provide strategic recommendations, solve complex problems, and lead key initiatives. As you grow, you’ll refine your analytical skills, take on leadership roles, and have the potential to transition into product management or data science based on your impact.

The interview process for a business analyst role at Google typically has five to six rounds, but it can vary based on the position and team needs. Here’s what you can expect:

Initial Screening

If your application catches their eye, you’ll have a phone interview with a recruiter or hiring manager. They’ll chat about your background, experiences, and why you’re interested in the role. They’ll also check if your vision aligns with Google’s culture. Note that recruiters might avoid discussing compensation and leveling details in this initial chat.

This round usually lasts about 30 minutes.

Computer Assessment Test

If you clear the initial screening, you’ll be notified within 2–3 days for the next round: computer assessment, where you’ll take a test with pre-recorded questions.

They’re looking to know how you tackle problems, especially with databases and writing efficient code. Be comfortable with window functions like RANK and DENSE_RANK, and know how to structure queries with CTEs, subqueries, and joins. Understanding star schema relationships and issues like cardinality and data bloat is key. You’ll also need to show you can profile data, manage query load, and explore schemas using meta-queries. Plus, be ready to troubleshoot any errors. Google prefers GCP BigQuery, so it’s worth checking the docs, even if it’s not always tested.

It’s also often timed to see how you handle pressure. While this isn’t always a part of the process, being prepared for a timed assessment is critical.

Technical Interview

After the assessment, you’ll have one or more technical interviews with a senior business analyst. Expect questions about SQL, Excel, R, Python, and your past projects. This round is usually done via Google Meet or Zoom. For instance, you might encounter SQL questions involving self-joins, running sum, and percentiles. This round typically lasts around 60 minutes. Some questions could be:

1. At Google, we often work with complex datasets. Given a table with Employee_ID, Manager_ID, and Name, how would you use a self-join to list employees alongside their direct managers? How would you optimize this query to ensure high performance when dealing with large datasets?

   Use a self-join to match Employee_ID with Manager_ID in the same table, aliasing the table to link employees with their managers. To optimize, index Employee_ID and Manager_ID and use EXPLAIN to analyze query execution plans for efficiency.

2. You are analyzing a customer dataset for Google Cloud’s business segment. How would you write a query to calculate the average purchase per customer segment, excluding those with a lifetime value below a set threshold, and ensure the query runs efficiently at scale?

   Write a query with GROUP BY to calculate the average purchase per customer segment, using a WHERE clause to exclude customers below the lifetime value threshold. Optimize by ensuring proper indexing on customer_segment and lifetime_value columns.

3. Google relies on clear data visualizations to tell stories. If you were tasked with presenting trends in user engagement over time for Google Ads, how would you use R or Python to create clear and actionable visualizations for business stakeholders?

   Use Python’s Matplotlib or Seaborn to plot time series graphs of user engagement trends over time, adding labels and annotations for clarity. In R, ggplot2 would help visualize these trends with customizable aesthetics and interactive options for deeper insights.

On-site Interview

If you make it past the technical interview, you’ll be invited to an on-site interview within a week at one of Google’s offices. This is a full-day event where you’ll meet multiple team members. It includes a mix of technical and behavioral questions, a case study presentation, and informal discussions. Expect a variety of questions and be ready for an intense schedule.

Some behavioral questions that you may expect are:

1. What are your three biggest strengths and weaknesses you have identified in yourself?

For strengths and weaknesses, focus on qualities relevant to data analysis and problem-solving. Show self-awareness and explain how you’re improving weaker areas.

2. How would you convey insights and the methods you use to a non-technical audience?

Explaining insights to a non-technical audience requires avoiding jargon and using relatable analogies. Focus on impact rather than process.

3. Describe a data project you worked on. What were some of the challenges you faced?

A data project challenge could involve messy data, unexpected trends, or stakeholder alignment. Explain how you approached the problem and what you learned.

4. Why did you apply to our company?

Express interest in Google by highlighting its culture of innovation and passion for data-driven decision-making. Mention specific products or projects that align with your skills.

5. What is your approach to resolving conflict with co-workers or external stakeholders, partially when you don’t really like them?

Resolving conflicts professionally means focusing on facts, maintaining open communication, and finding common ground. Share an example of a successful resolution.

6. How do you prioritize multiple deadlines? Additionally, how do you stay organized when you have multiple deadlines?

Managing multiple deadlines requires prioritization methods like the Eisenhower Matrix. Mention tools like Trello, Google Sheets, or time-blocking techniques to stay organized.

Case Study

You’ll get one or more case studies to analyze and solve. These reflect real challenges Google faces. After analyzing the case, you’ll present your findings to an interview panel. For example, you might be asked to measure spam or unfair use of a Google product like Chrome. This part can last around 50 minutes and requires you to think on your feet.

Googleyness Round (Bar Raiser)

This is the vibe check round. They delve deep into your past experiences, asking about handling disagreements with managers, dealing with underperforming team members, and more. This round typically lasts around 45 minutes. Expect questions designed to understand how you fit within Google’s culture and handle various workplace scenarios.

Final Call

After maneuvering through these rounds, you might get the final call in about a week. This call can be exciting, but be prepared for the compensation offer, which might be lower than expected. It’s essential to weigh the offer against your long-term career goals.

In your Google business analyst interview, you’ll face technical questions about SQL, Excel, and visualization tools like Tableau and Power BI. They’ll ask about product-market and statistical analysis as well. Don’t forget behavioral questions about handling situations. Google tends to hire the best talent—not just the technically skilled but also those who are adaptable and a good fit culturally. Here is a list of questions previously asked at interviews:

Google Business Analyst SQL Questions

SQL is essential for Google business analysts because they work with large datasets and need to extract, clean, and analyze data efficiently. Questions test your ability to write queries, manipulate data, and generate insights that drive business decisions. A strong grasp of SQL ensures analysts can work seamlessly with databases and provide accurate, data-driven recommendations.

1. Given two tables, attribution and user_sessions, calculate the first touch attribution for each user who converted. The first touch attribution is the channel associated with the user’s first session when they discovered the website.

   For first-touch attribution, use window functions like ROW_NUMBER() or RANK() to find the first session for each user. Then, join this with the conversion data to determine the channel from the first session.

2. Given a table google_searches with user_id, search_query, timestamp, and device_type, write a query to calculate the average number of searches per user per day.

   Use DATE(timestamp) to extract the day and COUNT(search_query) to determine the number of searches per user. Group by user_id and calculate the average searches per day.

3. From a table of flights, find the 2nd longest flight (by duration) between each pair of cities, considering (source_location=X, destination_location=Y) and (source_location=Y, destination_location=X) as the same pair. If there are fewer than two flights between two cities, exclude them. Order the result by flight id in ascending order.

   For the second-longest flight, use LEAD() or DENSE_RANK() to rank flights by duration for each city pair. Exclude pairs with fewer than two flights and select the second-highest-ranked flight.

4. Given a table of bank transactions with user_id, transaction_value (positive for deposits, negative for withdrawals), and created_at, write a query to calculate the three-day rolling average of deposits grouped by day. Format the date in the output as '%Y-%m-%d'.

   To calculate the three-day rolling average of deposits, first filter transactions to include only deposits. Then, use a window function with a date range to compute the rolling average while ensuring proper formatting of the date.

5. From a table of product subscriptions with user_id, start_date, and end_date, write a query to determine if each user has a completed subscription (where end_date is not NULL) that overlaps with any other completed subscription. Return user_id and a flag (1 for overlap, 0 otherwise).

   To detect subscription overlap, perform a self-join on user_id where start_date and end_date overlap. Use a CASE WHEN statement to flag users who have overlapping completed subscriptions.

6. From a table google_customer_activity with customer_id, activity_timestamp, and activity_type, write a query to find the most frequent activity type for each customer.

   Use GROUP BY and COUNT(activity_type) to identify the most frequent activity for each customer_id. You can use RANK() or ROW_NUMBER() to return the most frequent activity type per user.

7. Using employees and projects tables, identify the five lowest-paid employees who have completed at least three projects. A project is considered completed if End_dt is not NULL. Return the employee_id of these employees.

   To find the five lowest-paid employees who have completed at least three projects, filter employees based on completed projects (End_dt IS NOT NULL). Then, order the results by salary in ascending order and select the top five.

Google Business Analyst Product Metrics Questions

Understanding product metrics is critical for evaluating the success of Google’s products, like Google Cloud, Drive, or Ads. You need to know which metrics matter, how to interpret them, and how to use data to optimize product performance. These questions assess analytical thinking and the ability to translate numbers into actionable insights.

1. A product manager decides to add threading to comments on group posts. We see comments per user increase by 10%, but posts go down 2%. Why would that be?

   An increase in comments but a decrease in posts suggests users are engaging more within existing discussions rather than starting new ones. Investigate if total interactions, including likes and replies, have increased to balance the impact.

2. You are a data scientist at YouTube focused on creators. A PM comes to you worried that amateur video creators could do well before, but now it seems like only “superstars” do well. What data points and metrics would you look at to decide if this is true or not?

   To analyze YouTube’s treatment of amateur creators, examine the distribution of views across different creator tiers. Check if algorithm changes have affected discoverability for smaller creators.

3. We want to specifically improve search results for people looking for things to do in San Francisco. What would you investigate, and what metrics would you come up with to understand if the current functionality in the search was performing well?

   Improving search results for activities in San Francisco requires analyzing click-through rates, bounce rates, and time spent on relevant pages. Optimize rankings using personalization and user behavior data.

4. Google Cloud’s new machine learning product has been launched. After three months, you observe that there’s a growing user base, but revenue growth has slowed. What metrics would you investigate to understand the potential issue?

   Investigate metrics such as customer lifetime value (CLV), usage frequency, retention rates, and the number of active users. It’s also important to analyze the conversion rate from free-tier to paid-tier users, as well as churn rate and customer satisfaction surveys.

5. Let’s say that you’re a part of the engagement team. A product manager comes up to you and says that the weekly active users metric is up 5%, but email notification open rates are down 2%. What would you investigate to diagnose what’s happening?

   A rise in weekly active users but a drop in email open rates could indicate users are engaging through other channels. Investigate if app notifications or in-app features provide the same information, reducing the need for emails.

6. You are analyzing user engagement for Google Drive. You notice that while the number of users has grown by 15% month-over-month, the average file size per user has decreased. What could explain this trend?

   This could indicate that users are uploading more files but of smaller sizes, possibly due to changes in user behavior or file types (e.g., more images and documents vs large video files). Investigate the types of files being uploaded and analyze user trends in storage consumption.

7. You’re tasked with improving the engagement rate for Google Photos. You observe that the retention rate is high, but users seem to be uploading fewer photos. What metrics would you analyze to understand this trend?

Investigate photo upload trends over time, retention of specific user segments, and the usage of key features like photo sharing, album creation, and search functionality. Look at the feature adoption rate to determine if any new updates may have impacted photo uploads.

Google Business Analyst Algorithms Questions

Although business analysts don’t write code daily, they need to think logically and solve problems efficiently. Algorithm questions test structured thinking, pattern recognition, and decision-making—key skills when analyzing data or optimizing business processes. Google values candidates who can break down complex problems and find scalable solutions.

1. Given two sorted lists, write a function to merge them into one sorted list.

   Merging two sorted lists efficiently requires using two pointers to maintain order in O(n) time without extra sorting.

2. Given two strings A and B, write a function can_shift to return whether or not A can be shifted some number of places to get B.

   Checking if one string can shift to become another can be done by seeing if the second string appears as a substring of the first string concatenated with itself.

3. Find and return all the prime numbers in an array of integers. If there are no prime numbers, return an empty array.

   Finding prime numbers in an array requires a helper function to check for primes, iterating through the array and returning only valid values.

4. Write a function isMatch(s,p) which takes in two parameters, the string and the regex pattern. It should return a Boolean output indicating a “match success” or a “match failure.”

   Regex matching involves recursion or dynamic programming to process special cases like. (any character) and * (zero or more of the preceding character).

5. Given a string, find the length of the largest palindrome that can be made from the characters in the string. A palindrome is a word, phrase, number, or other sequence of characters that reads the same forward and backward, ignoring spaces, punctuation, and capitalization.

   For the longest possible palindrome from a string, count character frequencies to determine symmetrical arrangements. Odd-count characters can appear only once in the palindrome’s center.

Google Business Analyst Virtualization Interview Questions

1. As part of the financial management in a large corporation, the CFO wants to review the expenses in all departments for the previous financial year (2022). Write an SQL query to calculate the total expenditure for each department in 2022. Additionally, for comparison purposes, return the average expense across all departments in 2022.

   To calculate total and average expenditures by department for 2022, filter the data for that year, group by department, and use SUM() to calculate total expenses and AVG() with an OVER() clause for the overall average. The query groups by department and orders the results by total expenditure in descending order.

2. In Excel, how would you build a dynamic dashboard that updates automatically based on changing data inputs?

   Provide a brief overview of how you would make a dynamic Excel dashboard. Discuss using Excel features like PivotTables for effective data organization and visualization. Additionally, mention incorporating interactive elements such as drop-down menus or slicers to enhance the user experience.

3. You’ve been asked to create a dashboard to monitor the success of Google Ads campaigns. What key metrics would you include in your visualization, and how would you present them to make the data actionable for stakeholders?

   Focus on metrics like click-through rate (CTR), conversion rate, cost per acquisition (CPA), return on ad spend (ROAS), and customer segmentation. Use bar or line charts for trends over time, pie charts for breakdowns of ad performance by device or campaign type, and heatmaps for geographic targeting.

4. Suppose you are analyzing data for Google Search to understand trends in user queries over time. What type of visualization would you use to show the change in search volume for different query categories over the last 12 months?

   A line chart would be best to show trends over time for different categories. You could use color-coding to differentiate between categories or use a stacked area chart to show the proportion of searches in each category over time.

Here is how you can enhance your chances of acing your Google business analyst interview:

Showcase Your Data-Driven Problem-Solving Skills

Google loves data! Highlight your skills with BigQuery, Looker, and Google Analytics. Share how you’ve used these tools to solve problems. Mention any projects where you’ve analyzed large datasets and made key decisions. Keep it simple.

The interview will focus on how you’ve applied data to solve real business challenges and make data-driven decisions that impact teams across the company.

Demonstrate Strong Collaboration and Leadership Skills

Teamwork makes the dream work at Google. Talk about times you’ve worked with diverse teams—including engineers and product managers. Share how you led projects or initiatives without being the boss. Show how you used Google Workspace or Jira to keep everyone in sync.

Prepare for Business Case Studies and Problem-Solving Scenarios

Expect to face case studies or business scenarios that require clear, analytical thinking. These tests will assess how you approach problems, structure your analysis, and communicate solutions. Use the STAR method (situation, task, action, result) to present your thought process and how you’d approach real-world business challenges.

Google might ask about improving a service like YouTube or Google Maps. Use a clear approach: understand the problem, analyze data, and suggest practical solutions. Think about how your ideas improve user experience.

Expect Behavioral Questions

The interview will likely include questions about how you handle ambiguity and pressure, as these are key aspects of the fast-paced environment at Google. Be prepared to discuss situations where you’ve worked through uncertainty, prioritized tasks under pressure, and focused on delivering results.

Align with Google’s Mission and Values

Lastly, Google is looking for candidates who align with its mission to make information universally accessible and useful. Emphasize your passion for innovation and data-driven decisions and how your values reflect Google’s focus on creating impactful solutions that reach millions of users worldwide.

Landing a business analyst role at Google is an opportunity to solve complex challenges and make a global impact. To prepare, focus on technical skills like SQL, Python, and data visualization while honing your ability to draw actionable insights from large datasets. Expect case studies, problem-solving scenarios, and behavioral questions that test how you collaborate, handle ambiguity, and align with Google’s mission to innovate and empower users. All the best!