Ask "what's the best interview prep app for data analysts?" and you mostly get SQL platform lists. That answer is half right. SQL is the gate. A shaky join or a botched window function ends the loop early. But passing the SQL round only gets you into the room where the offer is actually decided.
That room is a hiring manager asking how you'd investigate a 10% drop in conversions, a panel watching you present a take-home to people who don't read SQL, and a behavioral round that asks when your analysis changed a decision. Those rounds reward something SQL platforms don't train: explaining an insight out loud to people who have to act on it.
So here's the honest comparison. For SQL drilling, use a dedicated SQL platform. For the stakeholder, case, presentation and behavioral rounds, Revarta is the best interview prep app for data analysts in 2026. The strongest prep uses both.
Quick start: Try Revarta free. Answer "tell me about a time your analysis changed a decision" out loud and see how hiring-manager-grade feedback compares with the polite version you get from a chatbot. Free to start: 2 full mock interviews and 2 practice questions.
What data analyst interviews actually test
Before comparing tools, get the framing right. Loops vary by company and level, but a typical data analyst process splits roughly like this (editorial estimates, not survey data):
- SQL and technical (25-35%) covers joins, aggregations, CTEs, window functions, deduplication and date logic, plus Excel or spreadsheet work (pivot tables, lookups) and sometimes Python or a BI tool. It's run live in a shared editor or as a timed take-home. It filters people out more than it separates the strong candidates.
- Product or business case (20-25%) sounds like "metric X dropped 10% week over week, what do you do?", "how would you measure the success of this feature?" or "which metrics would you put on this team's dashboard?" It tests structured thinking and business judgment.
- Statistics and experimentation (10-15%) covers A/B testing basics, significance, sample size, p-values in plain English, and when not to trust a test result.
- Take-home and presentation (10-20%) means analyzing a dataset, then presenting findings to a panel. It's scored as much on the story and the recommendation as on the analysis.
- Behavioral and stakeholder (20-30%) includes "a time your analysis changed a decision," "pushback from a stakeholder," "messy data under a deadline," "a time you were wrong" and "how you prioritize competing requests." This round decides between candidates who all passed SQL.
SQL is the most tool-friendly bucket. Queries have right answers, a platform can grade them automatically, and several good ones do exactly that. The case, presentation and behavioral buckets are about communication, and a query grader can't help there. You need someone (or something) to listen and push back.
Quick comparison
| App | Best for | SQL depth | Communication and behavioral coaching | Price |
|---|---|---|---|---|
| Revarta | Behavioral, stakeholder, case and presentation rounds | Out of scope (no SQL execution) | Hiring-manager-grade, voice-first | $39/mo, $99 for 90 days |
| DataLemur | Focused SQL interview drilling | Excellent | None | Free tier; Premium $15/mo or $60/yr |
| StrataScratch | Large bank of real company SQL and Python questions | Excellent | Light (AI mocks focus on coding) | Free tier; check current pricing |
| Interview Query | Broad data interview coverage (SQL, product, stats) | Very good | Mid (paid human coaching extra) | Check current pricing |
| LeetCode (Database) | SQL reps for people already on LeetCode | Good | None | Free tier; Premium paid (check current pricing) |
| DataCamp | Learning SQL and analytics from scratch | Strong for learning | None | Free Basic; Premium paid |
1. Revarta: best for the rounds that decide data analyst offers
What it is. An AI interview coach built by a former Google, Amazon, and Adobe hiring manager who has run 1,000+ interviews. You paste a job description and your résumé, and it builds a prep plan for that specific job: a fit score, your strengths and gaps, the interview rounds you're likely to face with interviewer personas, and company research. Then you practice the way the interview actually happens. You speak your answers out loud in voice-first mock interviews or on single practice questions, and you get feedback calibrated to what hiring managers weight.
What it does not do. Revarta doesn't run SQL, check query output, or grade your code. If you need reps on window functions, that's a job for the platforms below. We'd rather say that plainly than have you find out mid-prep.
Why it wins the non-SQL rounds. In analyst interviews, the gap between "competent" and "hire" is usually the so what. Interviewers listen for whether you lead with the decision or bury it under methodology, whether you name the tradeoff, and whether your stakeholder story shows influence or just compliance. Story Builder (/star-stories) is a voice coach that helps you turn your real experience into STAR stories and maps them to the questions you're likely to get, including the ones that show up in nearly every analyst loop:
- Analysis that changed a decision. The question behind it: did your work move money, roadmap or headcount, or did it end up in a deck nobody opened?
- Stakeholder pushback. When a director disliked your numbers, did you defend the method, re-check the data, or fold?
- Messy data under a deadline. What did you ship, what caveats did you attach, and what did you refuse to ship?
- Being wrong. An analyst who has never been wrong hasn't shipped much. Interviewers know that.
- Explaining to non-technical people. Can you explain a confidence interval to a VP in two sentences without saying "statistically significant" five times?
You can also run the product case out loud. "Signups dropped 10%, walk me through it" is a spoken reasoning exercise, and answering it in your head isn't the same as saying it under time pressure. The coach follows up between sessions, so prep keeps moving without you managing it.
Coverage. Data analyst, senior and lead analyst, product analyst, BI analyst and analytics roles, plus adjacent loops with the same behavioral layer: data scientist, business analyst, marketing analyst, data engineer and data analytics consultant. Role-specific question sets are on the data analyst interview page.
Pricing. $39/month, $99 for 90 days, or $349 lifetime (see pricing). Free to start with 2 full mock interviews and 2 practice questions. The Job Description Decoder and Tell Me About Yourself builder are free and need no signup.
Best for. Analysts who can write the query but freeze on "so what would you recommend?", career switchers translating earlier work into analyst stories, and senior candidates whose loop leans on influence and judgment.
Try Revarta free: practice a data analyst behavioral question →
2. DataLemur: best for focused SQL interview drilling
What it is. A SQL-first interview practice site created by Nick Singh, co-author of Ace the Data Science Interview. It offers interview-style SQL questions tagged to companies like Facebook, Google and Amazon, an in-browser SQL editor, and a smaller set of statistics, probability and ML questions.
Strengths. Tight, interview-realistic SQL problems with hints and full solutions. Free resources include a SQL tutorial and a 9-day data interview crash course. Premium is inexpensive: $15/month or $60/year, and a $300 package adds a one-hour call with Nick Singh and a signed copy of the book.
Limitations. It's built to sharpen SQL, not to coach spoken answers. There's no behavioral practice, no stakeholder-scenario feedback and no presentation coaching.
Best for. Anyone with a SQL screen on the calendar. For many analysts, DataLemur plus a speaking-practice coach covers the whole loop.
Stop Guessing. See Exactly How You Sound.
Reading about interviews won't help you. Speaking out loud will. Your first few interview practices on us.
Get specific feedback on what's working and what's killing your chances. Know your blind spots before the real interview.
3. StrataScratch: best for the biggest bank of real company questions
What it is. A data interview platform with 1,000+ coding and concept questions drawn from real company interviews, covering SQL and Python, plus 350+ non-coding concept questions on statistics, probability and modeling.
Strengths. Breadth and realism. Free SQL and Python learning paths let you start without a credit card. It also offers AI-powered mock interviews that score code quality, correctness and communication, which helps when you're explaining a solution while you write it.
Limitations. The mock interviews are centered on technical problems. You won't get deep coaching on the behavioral round, stakeholder stories or the take-home readout. Pricing has changed with promotions during 2026, so check current pricing before you buy.
Best for. Candidates who want maximum SQL and Python volume, especially those interviewing at large tech companies.
4. Interview Query: best for broad data interview coverage
What it is. A data science and analytics interview platform covering SQL, Python, product metrics and case questions, statistics, machine learning and take-home challenges, with company-specific interview guides. One-on-one coaching with data practitioners is sold separately.
Strengths. One of the few platforms that treats the product case and statistics as first-class content rather than an afterthought. The take-home challenges are good practice for the analysis half of a presentation round.
Limitations. It's more expensive than SQL-only sites, and listed prices have varied, so check current pricing. Human coaching costs extra per session. The behavioral layer is content you read or pay a coach to practice, not unlimited spoken practice.
Best for. Product analyst and data scientist candidates who want SQL, case and stats in one place and have room in the budget.
5. LeetCode (Database problems): best if you already live on LeetCode
What it is. The coding-interview giant's database section, including the SQL 50 study plan, which walks from basic SELECTs through joins, aggregation, subqueries and string functions.
Strengths. Structured SQL reps, many on the free tier, with large community discussion threads. It's the natural choice if you're also prepping Python or coding rounds for an analytics engineering or data science role.
Limitations. The problems are puzzle-shaped more than business-shaped, and some are locked behind Premium. There's nothing for case, presentation or behavioral rounds.
Best for. Analysts targeting technical-leaning roles who want SQL and coding practice in one account.
6. DataCamp: best for learning the skills before you interview
What it is. A learning platform with courses, projects and career tracks, including the Associate Data Analyst in SQL track (11 courses, about 39 hours) and industry certifications such as Power BI Data Analyst.
Strengths. The best on-ramp here for bootcamp grads and career switchers who are still building SQL, spreadsheet and BI fundamentals. The free Basic plan includes the first chapter of every course.
Limitations. It's a learning platform, not interview practice. Finishing a track doesn't prepare you to defend an analysis under questioning.
Best for. Career switchers who need to learn the skills first, then move to interview drilling.
What about ChatGPT for data analyst interviews?
ChatGPT is a good SQL tutor. Ask it to explain ROW_NUMBER() vs. RANK() and you'll get a clear answer.
It's an unreliable interviewer. Chat assistants are trained to be agreeable, and that's a problem when you're testing your answers against people who aren't. Give it a vague answer to "DAU dropped 10%, what do you do?" and it will probably call your approach thorough. A hiring manager listens for whether you:
- Checked whether the drop is real (a tracking change, a holiday, a pipeline outage) before analyzing anything
- Segmented by platform, region, cohort and acquisition channel instead of guessing
- Separated what the data shows from what you're inferring
- Ended with a recommendation and next step, not a list of things you'd "look into"
The same goes for stakeholder stories. "I aligned with stakeholders and we moved forward" sounds fine to a chatbot. To an interviewer it sounds like nothing happened. Feedback that's free but wrong costs more than feedback that's right. Full breakdown: Revarta vs. ChatGPT for interview practice →
How to prepare: a 3-week data analyst prep plan
Career switchers should stretch this to 4-6 weeks and give week 1 extra time.
Week 1: SQL and statistics foundation.
- Do 30-50 interview-style SQL problems on DataLemur, StrataScratch or LeetCode's SQL 50. Prioritize joins,
GROUP BYandHAVING, CTEs, window functions, and date and retention logic. - Refresh A/B testing basics: hypothesis, sample size, significance, and common pitfalls like peeking and novelty effects.
- Paste your target job description into the JD Decoder to see which skills and rounds to weight.
Week 2: Stories and the product case.
- Use Story Builder to draft 6-8 STAR stories: analysis that changed a decision, stakeholder pushback, messy data under deadline, being wrong, prioritizing competing requests, and explaining something technical simply. The STAR method mastery guide covers the structure.
- Say each story out loud 3-4 times and get feedback. Cut the methodology, keep the decision.
- Practice 4-5 metric-drop and "how would you measure X" cases out loud.
Week 3: Pressure practice and the presentation.
- Run full Revarta mock interviews several times this week, mixing behavioral, case and stakeholder questions.
- If there's a take-home, rehearse the readout out loud: recommendation in the first 30 seconds, three supporting findings, caveats, then next steps.
- Prepare a sharp answer to "tell me about yourself" with the free Tell Me About Yourself builder.
Common data analyst interview questions to practice
Behavioral and stakeholder.
- Tell me about a time your analysis changed a decision
- Describe a time a stakeholder pushed back on your findings
- Tell me about working with messy or incomplete data under a deadline
- Walk me through a time you were wrong about something in the data
- How do you prioritize when three teams want analysis this week?
- Explain a technical concept to a non-technical audience
- Tell me about a dashboard or metric you built that people actually used
- Why data analytics? (for career switchers, why now?)
Product and business case.
- A key metric dropped 10% week over week. What do you do?
- How would you measure the success of a new feature?
- Which metrics would you track for a subscription business?
- An A/B test shows a lift, but revenue fell. How do you interpret it?
SQL and technical.
- Find the second-highest value per group
- Calculate 7-day rolling averages
- Compute month-over-month retention by cohort
- Deduplicate records and explain your tie-breaking logic
Drill the SQL list on a SQL platform. Practice the first two lists out loud, because that's where the question behind the question matters most.
Bottom line
For 2026, the best interview prep app for data analysts is a stack: a SQL platform (DataLemur for focus, StrataScratch for volume, Interview Query for breadth) plus Revarta for the behavioral, stakeholder, case and presentation rounds that decide who gets the offer.
The cost comparison isn't with other apps. It's with a missed offer and another month of searching, or with a human interview coach at $200-500 an hour. Revarta's 90-day plan costs $99.
Try Revarta free: practice your next data analyst interview question →
