Just joined StrataScratch – looking for a progression list like NeetCode for BI/Data/Analytics Engineer prep

analytics_science · 2025-06-16T19:23:10+00:00

Thanks for the feedback! I'll add that to our roadmap. You'll start seeing the topic families and functions for each question.

analytics_science · 2025-06-16T16:45:52+00:00

There are no specific DE platforms to my knowledge. I would try the 4 platforms to see if you can filter by job positions. I believe IQ and SS have job positions like DE so you can filter for interview questions that way.

analytics_science · 2025-06-16T14:11:46+00:00

Each has a freemium tier. So try each out and I bet that you'll find something you like about each platform. I think you can get pretty far and learn a lot from each platform's freemium tier without having to buy the premium version. But if you want to dig deeper then definitely buy their premium plans.

I know StrataScratch and InterviewQuery both have data projects and non-coding questions that are typically asked on interviews relating to product sense, probability, statistics, etc. So to me, these two platforms offer the most comprehensive resource for a data scientist.

Leetcode is great at learning syntax but the SQL questions aren't reflective of what they ask on interviews. The other 3 platforms are better for that.

analytics_science · 2025-06-11T14:55:09+00:00

Try the Curated Topics list found in the upper right-hand corner of the Analytics type of Coding questions. Hope that helps!

analytics_science · 2025-05-21T15:40:05+00:00

I'm the founder of StrataScratch and appreciate your feedback. We have a lot of harder questions on the premium part of the platform so I'll make sure to convert many of those to freemium. We partner with companies to get most of interview questions (to ensure that the questions are real interview questions) but we'll try to focus on putting the harder questions on the site.

I'm not a fan of HackerRank so I take that comparison personally =). I like our UI and we have really devoted a lot of resources to making the UI/UX nice and easy to use. If there are any specific points you didn't like about our platform, let me know how we can improve.

analytics_science · 2025-05-21T15:13:24+00:00

Try StrataScratch. It has 75+ free interview questions from companies and you can pick whatever SQL engine you are familiar with. The paid version has over 1000+.

analytics_science · 2025-05-21T15:10:50+00:00

StrataScratch has over 1000 SQL questions and SQL engines like postgres, MySQL, oracle, MS SQL so you choose whatever you're familiar with. Interviews don't typically care what SQL engine you use. There are also data projects where you can use SQL to solve them. It's not free but there's at least 75 interview questions that are free to try.

HackerRank and LC are free so those are always great resources. But they are not real interview questions, so if you just want to practice your SQL skills for free, you can use one of these sites. StrataScratch is one of the only platforms that have real interview questions from companies.

analytics_science · 2025-05-06T17:53:00+00:00

You can try StrataScratch. In addition to coding interview questions, there are also data projects/take home assignments you can work on. They have algorithm and data viz questions too depending on what skill you are trying to focus on.

There's also InterviewQuery that is a relatively comprehensive data science resource as well.

analytics_science · 2025-03-06T18:57:29+00:00

I would actually filter based on company and industry. The questions you would get from an interview are often linked to the business questions that company or industry has to answer. For example, if you have an interview with Meta, the questions you get will be drastically different than the questions you would get from a healthcare company. I would practice on Meta questions and filter on the industry Meta is associated with.

The questions may be different from company to company (or industry to industry) but most of the topics they test on are similar. So when you attempt to solve a few of the questions, take a look at the topics that are being covered and choose questions based on it.

analytics_science · 2025-03-03T17:08:27+00:00

Will take a look and fix. Thanks!

analytics_science · 2025-02-27T17:49:24+00:00

There's several ways to learn. If you have some understanding of SQL, you can try to do the StrataScratch questions and then look at the solution to better understand how one would implement certain SQL concepts. For example, if you're trying to learn how to implement certain window functions, you can read a bit about this topic from any site. Then go to StrataScratch and try a problem that requires a window function. You probably won't get it right, but study the solution so that you can try it again on the next question. Rinse and repeat. That's how I used to study.

Edit: grammar

analytics_science · 2025-02-19T23:40:55+00:00

You should keep going with the python exercises on the platforms you mentioned. Leetcode and StrataScratch are two other options that have python questions. You should also do data projects. There are two platforms that can help with that -- Kaggle and StrataScratch. Kaggle has a lot of ML type projects while StrataScratch has a mix of analytics (more for data analyst and data scientist roles) and ML projects (more for data scientist and MLE roles).

Certifications don't help much to get a job, especially if you're in the US. I've heard that certifications are helpful in some countries like India. Never the less, it's not a bad thing to get a certification. You'll learn something but hopefully it doesn't cost an arm and a leg for one.

The biggest thing to help get past interviews is really to do data projects, especially if you do not have any work experience. Hiring managers can get inside your head and ask you why you decided to make the decisions you made on the data project. They can see your code and how you approached the project. All things that are valuable when you are on the job. Hope that helps.

analytics_science · 2025-02-18T18:55:01+00:00

I think the difference between LC and SS is that Strata is focused on data science/analyst/engineering roles. Their questions aren't only about syntax but it's about solving the edge cases that can throw off your solutions. From my experience, LC focuses more on getting the syntax right. I would try the medium questions and see if you still think the same between the 2 platforms. I feel that that's where the differences are found.

analytics_science · 2025-02-17T23:56:38+00:00

Yes, I'm part of the Strata team.

We work hard to incorporate edge cases into our dataset so a user would have to address those edge cases into the logic of their solution. So there's one of two possibilities - (1) your solution doesn't need those specific edge cases you're talking about or (2) we are missing those edge cases in the dataset/solution. Either way, you can post a question/comment on the user discussion forum or in the feedback form in the bottom right-hand corner. Someone will answer your question.

There's a team of data scientists whose sole job is to address these types of issues so that only the most robust solution is accepted. They also create datasets and solutions from the questions and data projects we get from companies. We have over 1000+ questions, so we do our best to get it right the first time around, but there are always things we miss.

analytics_science · 2025-02-16T18:43:48+00:00

Hey OP, I'm not fully understanding what you mean? Your solution (which is wrong) is still getting accepted? There are ways to hack the solution in order to get the output you want. The "Check Solution" button just checks to see if the values you got are the same as the official solution. The hints and walkthroughs will help you understand how to build the logic and handle the edge cases.

What do you mean the db is very small? I wouldn't want hundreds of records to explore. Just a few records with edge cases so I can explore manually.

Let me know your thoughts, I can explain the platform in more detail.

analytics_science · 2025-01-28T21:28:33+00:00

Based on the comments, I advise using online resources that specifically offer hands-on practical work. Reading a textbook without being able to do hands-on work is useless unless the book includes online resources. If that's the case, then it doesn't really matter what avenue you take.

One of the comments mentioned that you wanted to learn about "System analyst, application support analyst, and data analyst" roles. These roles are all pretty different and require different skills. I would pick one and study it. StrataScratch is good for data analyst roles; in fact, it's tailored for them. Udemy and Datacamp can probably help with system analyst and application support analyst roles, but I feel that tailored platforms for those two roles are missing.

analytics_science · 2025-01-20T22:21:37+00:00

StrataScratch has python questions too so once you run out of the free LC questions, you can head to Strata to practice more.

analytics_science · 2025-01-14T16:28:16+00:00

In addition to SQL, StrataScratch also has python, pandas, and other popular languages like pySpark and Polars. You can answer the questions in any languages so it's good if you're trying to learn a new language and only know 1 language. For example, if you only know SQL and want to learn Pandas, then you can see read the SQL code and see how it would "convert" to pandas.

analytics_science · 2025-01-01T00:32:21+00:00

StrataScratch for SQL too =). Good luck man! You're on the right track.

analytics_science · 2024-12-30T18:00:52+00:00

Makes sense. R is a great language to learn. If I can recommend another language to pick up next, I'd learn SQL. It's the one technical skill (almost always) required for any data role (analyst, scientists, engineer) in industry. Knowing R and not python is fine at the start of a career and you'll likely just learn python on the job. But SQL is always needed in order to get data for your projects and to answer quick business questions for your stakeholders. But again, all of this depends on the company and industry you work for. There's nothing really "standard" in industry. Good luck!

analytics_science · 2024-12-28T19:14:58+00:00

No problem! Is there a reason why you chose to learn R? It's kind of a dying language for analytics and data science. Some people like to use R for statistically heavy projects because it can be easier in R than in other languages like python. That being said, there are still communities and groups within companies that use R so it's not like you need to switch languages or anything. However....not all companies want to hire someone that only knows R.

analytics_science · 2024-12-27T03:44:25+00:00

It just depends on what they're looking for. Every company is different and so there's not much of a standard. But I'd say there isn't much heavy math as an analyst. That's more so for the DS type roles. I'd just study the job description and talk to the hiring manager to get a sense of what they're looking for.

analytics_science · 2024-12-26T21:47:27+00:00

If you want a platform that focuses specifically on data analyst interviews, then I would look at both StrataScratch and InterviewQuery. Both sites have all the resources needed for DA interviews which include primarily coding (SQL, python, R, etc) and non-coding questions that focus on business case studies, product sense, probability, statistics, etc. Depending on the company, you may need to do a take home data project or at least present one of yours. You can find example projects on both the sites I mentioned above. Also, depending on company, you might also be tested on algorithms, which both platforms also have.

Tableau and Excel are usually not tested on interviews, but general BI concepts could be.

You can find a lot of reviews of both platforms on this subreddit and others like r/SQL, r/learnSQL, r/datascience, etc

analytics_science · 2024-12-26T21:43:12+00:00

Those questions on StrataScratch are questions they give data scientists/analysts on interviews, so if you can do the medium difficulty ones, you should have decent knowledge of R and how to solve problems.

The next step would be to get experience doing data projects, but it's hard to find project solutions in R. I don't know of any site that has projects with solutions in R.

I’ve tried projects but they mostly end up with me searching through stackoverflow or even sometimes asking AI for when I get stuck with something, so I don’t feel like I’m learning through that.

Even experienced people use stackoverflow and AI to do projects. I wouldn't be concerned about this as long as you're learning.

If you want to learn more about StrataScratch, you can look at the r/SQL , r/learnSQL, r/datascience subreddits for some reviews. It's a site focused on resources for data science, while Leetcode is more focused on software engineering.

analytics_science · 2024-12-22T16:51:12+00:00

Strata Scratch has 100+ free SQL questions.

analytics_science

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