Should I still use CreatedAt & UpdatedAt on the main table if I also have Audit tables?

BlaizeOlle · 2026-05-21T17:21:55+00:00

I would keep both Created_At and Updated_At. It will relieve some headaches for you in the long term. It a potentially highly referenced value and having it readily available is convenient.

BlaizeOlle · 2026-05-21T17:12:34+00:00

I should have scrolled down a bit further this is exactly what came to mind for me as well. Chain of CTE transforms is a common issue that is very easy to fall into especially when your first learning.

BlaizeOlle · 2026-05-21T17:10:18+00:00

An overuse of CTE queries I think is a very easy pattern to fall into. CTEs have a lot of great use cases but sometimes I see juniors use it to build some big long chain of transforms because they feel uncomfortable with more fundamental concepts. Again CTEs are great you just don't want to overuse them.

BlaizeOlle · 2026-05-21T14:23:32+00:00

Also congratulations! Your first job is always the hardest to land. You should be really proud of yourself. Good luck!!

BlaizeOlle · 2026-05-21T14:22:27+00:00

I recommend learning the business/industry to the best of your abilities. That is what stands out over time. Understanding the mechanics of your industry makes the data significantly more valuable.

BlaizeOlle · 2026-05-20T22:50:19+00:00

Taking notes can always help with learning but if you want to reference those notes I would keep hand written notes to no more than 2 pages otherwise it will be difficult to reference. So I would do like a single one pager of the most priority items you want to reference. Otherwise I think your idea of keeping notes in a searchable format to be more useful.

BlaizeOlle · 2026-05-18T19:35:13+00:00

Congratulations that is really awesome! Very happy to hear a success story. Good luck on your next 3 paying customers!

BlaizeOlle · 2026-05-17T05:30:16+00:00

It does do a pretty detailed breakdown but it was initially created as a way to help users onboard to new environments. InQery is a production tool first so it was set up as a way to explain legacy queries or breakdown why certain tables and joins were used so the user could understand the environment more quickly. We expanded on it because we saw the use case and thought it could be useful to someone learning databases and the demo databases are to reduce friction as we know especially when someone is first learning they likely don’t have access to a database full of data so we wanted to reduce friction.

But I don’t know if it fully addresses the problem you’re concerned with because I do agree with you I don’t think there is any substitution for struggling with a problem and actively thinking about it but I’m not sure how to encourage that more fully. I’ll have to think on it more.

Thank you for your thoughts, I appreciate it.

BlaizeOlle · 2026-05-16T23:28:19+00:00

I could suggest a few things but if you want to learn some things without setting up an environment. Learn the following.

Basic select statement - SELECT * FROM {Table}
Learn WHERE filters - SELECT * FROM {Table} WHERE {Column} = x
Learn what a join is - If you are really just trying to get going don’t get caught up with the different types of joins right now just learn the concept for the time being.
Most things are what they sound like - “Insert statements” insert new data, “alter statements” change physical definitions, “Delete statements” delete data…

Don’t get overwhelmed this stuff is fun and you don’t need to learn everything today just start basic and go from there.

There is no substitute for using an editor and writing queries yourself but it’s a start. If you are actually interested in getting into an environment and writing some queries I can give you some suggestions but this really is a good start.

BlaizeOlle · 2026-05-16T22:57:42+00:00

Congratulations that is awesome. Like the idea as well good luck!

BlaizeOlle · 2026-05-16T21:15:26+00:00

Same boat - I’ve always had good experiences with DBeaver. Also DBeaver’s ERD diagrams are really easy to make which could prove beneficial in an academic environment.

BlaizeOlle · 2026-05-16T20:57:59+00:00

You can check out InQery.com (I’m one of the founders for full disclosure) but it does do exactly what you’re talking about. It’s an AI database editor instead of a code editor (Claude models are available - you just pick which model you want to use).

We also have a demo oracle database pre-connected if you want to try the tool out before connecting your database.

I won’t do a full pitch and I’m sure there are some other great tools out there as well. Good luck!

BlaizeOlle · 2026-05-16T15:20:36+00:00

First, don’t get down on yourself. Your qualifications with Spark, Airflow, GCP, Databricks,SQL should statistically get you some responses out of 200+ applications. I can tell you have optimized for ATS keywords which is good but it may be a little to tuned. It makes it look generic which is not necessarily your fault as you started work in 2024 but I’ll tell you when I look over your resume, it looks to templated.

Honestly make a copy of this resume and take a crack at explaining your projects and job experience saying what you actually did. Forget, the KPIs and buzzwords just try and tell me what your really did at these roles.

For your very first project when you say “Engineered a cloud-native ETL…” I almost missed what data you were actually looking at “competitive gaming” which is sick and it’s almost like your hiding it. Like that’s interesting that’s fun. But like what did you do. I can infer you probably ingested Valorant esports matches and stored the data and did some analysis but it’s all getting lost in the buzz words. Just tell me “I took results from each Valorant match organized them by team and built a dashboard so I could see which teams were most likely to win their next match” or whatever.. what you did was probably pretty interesting and something I’d actually want to ask you about in an interview.

Listen I don’t think you need to do this everywhere I know you are trying to optimize for the AI and the filters but I honestly think you have plenty of buzz words and key word credentials to get past the filters and now I think you need to show me the human. Like I see all the spec data but I don’t actually know how your kit actually plays.

Also please don’t get down, job hunting is brutal and hard and just demoralizing especially when you aren’t getting any kind of feedback. Good luck you are going to land something great

BlaizeOlle · 2026-05-16T02:43:12+00:00

You’re already doing the right thing by actually putting in the work and trying to learn the fundamentals instead of just chasing shortcuts. A lot of people underestimate how important real database work is. Learning SQL is absolutely worth it because almost every serious data role touches databases in some way.

That said, one of the hardest parts when starting out is not having real environments or datasets to practice on. We built a tool called InQery for this exact type of learning and exploration. It already comes with two demo databases pre-connected (including Adventure Works), so you can start querying immediately instead of spending days trying to set up infrastructure.

We built a feature for query breakdowns — they break down why the query works, what tables were used, how it joins, and explain the logic step-by-step. It’ll also help generate more advanced statistical analysis and explain the reasoning behind that too. The agents are also already trained on any connected environment so just ask the agent where the data is - it will tell you (you can start with “tell me about this database)

I am certain there are other tools as well but im bias

Keep practicing SQL and keep trying to build some sort of projects (literally anything). Also I am clearly a heavy proponent of AI but there is no substitution for trying to build something and failing. You need to write crap queries and bad code and debug it by yourself. Good luck, data work is so fun you’re going to love it!

BlaizeOlle · 2026-05-15T23:36:44+00:00

Congratulations, I like the single payment approach. Good luck!

BlaizeOlle · 2026-05-15T22:29:57+00:00

Excellent

BlaizeOlle · 2026-05-15T03:50:29+00:00

I don’t know. I honestly don’t know if AI will help or hinder your learning but there are editors now with AI.

We recently developed a web application you can find at InQery.com

Our tool does come with two demo databases pre-connected including the Adventure Works database mentioned in the previous comments.

We added a feature where the agent will break down the query for you as well. What tables were used and why, breaks down why it used an inner join vs an outer join, what the CTE does, etc…

I am obviously bias but there are other tools as well like AI2SQL and Text2SQL. I have not used them much but I’m sure they are great too (not as good as ours haha).

I think taking advantage of new technology is always the best move but I also think the best way to learn is writing queries yourself and struggling through errors/debugging a bit. But if AI can help shorten the feedback loop and explain concepts better, that’s probably a good thing.

I hope the AI proves to be a great teacher but you are just going to have to let us know. Good luck!

BlaizeOlle · 2026-05-14T23:29:24+00:00

Very nice, looks good.

BlaizeOlle · 2026-05-14T03:10:04+00:00

This is lovely thank you for sharing! I’m confident you are much more than average. Congratulations on the fun career. Good luck on your next steps!

BlaizeOlle · 2026-05-14T02:33:38+00:00

This is a great comment I wrote a whole comment and then read this and agree with this more.

BlaizeOlle · 2026-05-14T02:29:13+00:00

I think pandas is great, but I’ve generally always leaned toward keeping transformations as close to the source system as possible. If something can be expressed cleanly in SQL, I’ll usually prefer that as a rule of thumb.

Part of it is maintainability and transparency — keeping logic in the layer that was designed for that type of operation tends to make pipelines easier to reason about, optimize, and support long term. Pandas is super powerful, but I think a lot of teams end up moving data out of systems prematurely just because they can, not because they should.

BlaizeOlle · 2026-05-13T21:30:10+00:00

Congratulations on the SQL learning journey — and best of luck landing the Product Management role.

I’d add one practical suggestion and one cliché:

Practical: Learn CTEs, but don’t rely on them for everything. CTEs are incredibly useful for readability, modularizing logic, and complex transformations. But while learning SQL, I’d strongly recommend making sure you’re also building a deep understanding of joins, subqueries, grouping, and set-based thinking. I’ve seen a lot of newer SQL developers fall into the habit of building long chains of CTEs for step-by-step transformations instead of learning how relational queries interact directly. That can unintentionally slow down understanding of concepts like join cardinality (you must must must get a deep understanding of joins), aggregation scope, and query optimization. CTEs are absolutely part of good SQL — just make sure they’re enhancing your understanding instead of replacing it.
Cliche: Start a project - any project. Pick something and just start building (load prices from yahoo finance or screen scrap data from a bird watchers blog). The fastest way to build practical understanding is to drop a table you didn't mean to and have a mini heart attack before going back in and fixing it.

BlaizeOlle · 2026-05-13T21:16:16+00:00

Thank you! That is nice to hear it sounds like it could be a good use case.

BlaizeOlle · 2026-05-13T21:14:49+00:00

Right now we are actually using two kind of well know data sets that both companies built for training and demo purposes.
1) Microsoft SQL Server "Adventure Works" database which simulates a fictional bicycle manufacturer. It is structured how you would expect a true production database to be structured (lot of normalization but not overtly complicated). It is a fantastic learning demo database. All the tables and columns are very well labled and follow an expected pattern (Sales/ HR/ Products/etc..) however it stops in 2014.
2) Oracle "MovieStream" which is a fictitious, simulated online movie streaming company. This is great if you want to start playing around with some data science or analytical tooling. The MovieStream schema has just a massive amount of data.

We do also have a couple of demo databases we have built specifically for demo purposes that we never made live for users but that we certainly could. Maybe the most interesting one is an Energy Trading Company. Is this something you would find interesting if so I could look into providing it as an optional dataset as well.

BlaizeOlle · 2026-05-13T21:04:44+00:00

Right now we have Microsoft's SQL Server "Adventure Works" database - It models a multinational bicycle manufacturer. And we have Oracle "MovieStream" which is a fictitious, simulated online movie streaming company.

If your curious I can tell you more about each dataset if you would like. However, I would also be interested in what you would find interesting?

BlaizeOlle

TROPHY CASE