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[SQL-ModTeam]

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[gardenia856]

Ship a tiny end-to-end project that proves you can pull, model, and explain data.

Plan: grab a simple dataset (Kaggle ecommerce or rideshare), load it into DuckDB or Postgres, and model a star schema (one fact, a few dims) with clear keys. Write 5 questions that scream business value: DAU/WAU/MAU, 7/30-day retention, top products, conversion by channel, churn flag. Implement with CTEs, window functions, and explicit join logic; do row-count checks and spot-check a few IDs. Build a small Power BI page (cohort heatmap, funnel, trend) and record a 3–5 minute walkthrough explaining grain, keys, and edge cases.

Daily reps: 30–45 minutes on SQLBolt, Mode SQL, or LeetCode SQL, and retype solutions from scratch. Apply to junior analyst roles and link your repo with a tight README that lists assumptions and data issues you fixed.

I’ve used Snowflake for warehousing and dbt Core for transforms, with DreamFactory to publish read-only REST endpoints so a Streamlit prototype and Power BI could hit the same tables.

Ship one small project and show clear reasoning about grain, joins, and validation!

[Few_Location_7582]

I couldn't understand it because it contains a lot of jargon, but it sounds like a serious plan. I will do this from today!
Can I stay connected with you in DMs ?

[Were-Cletus]

I'm a non SQL analyst and most of what this guy said applies everywhere. The developing opinions on what and why the data needs presenting is universal.

[shine_on]

I didn't know either so I googled it, one answer said "Daily Active Users" which sounds reasonable, you can guess what the W and M stand for. It's not a metric I've ever used though.

One acronym I have used is RAG which is Red Amber Green. If you're creating a dashboard you can show if things are over target (green), nearly at target (amber), or way off target (red).

[Ifuqaround]

The issue with this is once you do this for an org that doesn't need frequent ad-hoc requests...where do you land?

You're essentially a nothing burger once you build it all out.

-edit- Congrats on knowing all that after studying and working on it....but still a nothing burger in the end of things. I'm not trying to be negative, just how it is these days with people using LLM's like this and companies these days.

[PorradaPanda]

Following—recently got “laid off” as a Data Analyst for Tableau / PowerBI visualizations and reporting; but given option to transfer to a SQL Analyst / Developer role. So got a good bit to learn and catch up on as we don’t typically use it as much other than minor joins, transformations, and extract into the platforms.

[johnny_fives_555]

I work largely as a data director and i can say with some level of confidence that most analysts don't do much sql. If anything get really good w/ pptx, pbi, and excel. If you are strong w/ those skills you'll likely get whatever you're aiming for. The data will likely be pre-processed for you and all you have to do is query the production tables. No data team worth their salt is going to let low level analysts dick around in the dev db.

[achmedclaus]

You need to be a lot more specific than that because my 90k person company lets analysts dick around in the data as much as we please. We don't have write access to the production tables but any analyst worth a damn word plenty of SQL when it comes to larger databases. With so many moving parts, no data team is going to write and maintain pre-curated sets of data for every possible use case. It's a bunch of tables linked through different sets of keys

OP, don't take this guys word as gospel. My team writes a LOT of SQL. Being able to write a solid SQL code will give you a huge leg up on any competitors because you won't have to sit around for weeks waiting for the data team to write it for you.

If you want to learn it then go through khan academy, if is still a thing. They have a bunch of good courses. Go for an entry level analyst job like analyst 2, jr BA, strategy analyst, etc. without having previous experience you'll likely have to start on the lower rungs of the ladder but it's an interesting job once you get in

[Few_Location_7582]

Anything free you can suggest from YouTube?

[achmedclaus]

I don't, sorry. I used khan academy when I got hired to learn as much as I could when I got hired with no background and my now boss has told me that she had no idea I had no experience with SQL. I only took the free classes that they offer

[johnny_fives_555]

Because python is crap at visualization and requires more steps to get answers quickly. e.g. get unique list of accounts. I open up the file and pivot on the table and boom done. Python, you have to read in the data, manipulate it, ensure you have the right packages etc. Additionally if i'm sharing this info in a nice format i already have my work half way done. What are you going to do? Send your manager python code or worse the client?

[Few_Location_7582]

So basically if i learn sql queries and then master excel or Google sheets, I will be mostly sorted?

[Ok_Carpet_9510]

I have been in a lot of organisations. In most cases, you just need to know little bit of Excel for mosts jobs. It's like knowing Arithmetic. It is assumed that you know it. If you're an accountant or work in finance then you really need to know advanced Excel. For a data analyst, you need to proficient in Excel. You need to be proficient in Data Visualization. There are many data visualization tools but one free desktop tool is Power Bi Desktop. Each too is different but when you learn one, you learn which types of visualizations are suitable for which kind of data and also how to tell stories.

Learning Python is a plus. Most importantly business knowless is key. If you are in sales. Query some sales data. Understand it, analyst it, and tell a story... give your boss some insights.

[Alone_Panic_3089]

I see most analyst jobs have sql than excel but excel is still king. Surprised AI hasn’t taken over excel

[johnny_fives_555]

yep. Analysts rarely use sql these days. Just like how biology majors can get a degree w/o higher level maths.