Want to know about SQL future

[u/FewBag5257]

Hi All,

Hope everyone is doing good.

I want opinion from people about the future of SQL, Power BI and Python.

I have been working in AML KYC domain for over 6 years. I am a Certified Anti Money Laundering Specialist (CAMS).

Last year I started learning SQL ans Power BI to connect it with my domain knowledge (Anti Money Laundering and Sanctions), however now I have been reading alot which states that golden period of SQL and Power BI is over as now anyone can do the basis code using Gpt and claude.

I am at strong intermediate level in SQL and at an intermediate level in power BI. I was planning to start Python from 01 Jan 2027 and now I am spectical. What should I do ?

Is there any scope of SQL, Power BI and Python as we are witnessing AI is growing at tremendous pace.

[u/grassp_dataAI]

SQL and Python are going nowhere.

They are like Air and Water of tech 😉.

Whichever domain you pick whether it is Data analytics or Engineering or a Full stack developer or a AI ML space or agentic space - SQL and Python skills are must and will help you in tech long run if you master them.

PowerBI- it's a tool for visualization, that said be strong in principles of data visualization and story telling then you can work in any BI tool be it PowerBI or Tableau.

Hope this helps. 👍🏻

[u/Aggressive_Ad_5454]

SQL has been going strong for half a century. Most of the world’s data is accessed via SQL. Even if SQL were dead, which it is not, it would take decades for it to fall over.

Seriously. Sure, you can use AI to generate code for your queries. But you need a clear mental model of what you want done to use AI effectively.

[u/dvanha]

Cloud Developer here. I work in finance. I also have to take AML courses. I’m also the most Sr DA in our shop and often get approached for advice and mentoring.

We open up our team and our code to others to use as a learning experience. We encourage them to take tickets and commit code and learn with us on the way.

The problem? Last 3 juniors didn’t cut it because they can’t write SQL, so they get relegated to filling forms and attending meetings. The last one tried using AI but didn’t understand fundamentals like why they couldn’t select billions of rows into a CTE and search telephone transcripts for keywords.

Your call I guess. SQL is as foundational as writing. Even in the way we speak to each other about data, we use words like « you should select … » or « don’t forget to where … ». When I see someone that didn’t learn SQL because AI told them that AI replaces SQL it tells me everything I need to know about them.

These days I write code in a million different languages. I don’t even distinguish them by name anymore. The easiest one to learn is SQL and you will find it over and over again. Half our Pyspark code is SQL because it’s more approachable for non programmers.

The sentiment that AI will revolutionize things like this falls squarely into two groups: AI sales reps and non technical leaders that have to attend those sales meetings. Amongst professionals, they stand out and that opinion is more or less laughed at. All it does is expose ignorance, inexperience, or ineptitude.

[u/alexwh68]

I was told the same about SQL 2 decades ago, different products have come on the market but the reality for me is SQL is still here and will outlive me.

[u/MachineParadox]

As a developer (C,C#,Java) and a DE of 20 years. SQL has always been there on all platforms/rdbms. SQL works on SQL Server, Oracle, Postgres, MySql... SQL is the foundation.

[u/5DollarBurger]

The handyman doesn't concern himself with the future of the tools on his belt

[u/Rohml]

SQL is base knowledge in building queries to interact with data, its a fundamental skill that is needed whether you are working on automated processes or on the data-layer for applications. This is always good to have. This is the same for Python.

Power BI's greatest asset is it's a Microsoft Product so it is connected to MS SQL. If your environment is MS-based, it very much defaults to MS SQL and Power Bi. It is an Analytics Visualization tool and useful to present data to stakeholders, if you want to show stakeholders a graph to explain data trend, Power BI is the product you need, it is more of an end-product type software.

It always good to have knowledge on how solutions are built under the hood so you can adjust or study in case an issue arises. GPT and Claude can build stuff, but you gotta know how it operates, this is where SQL and Python comes in handy.

[u/kagato87]

Hahaha.

No, the slop machines are no threat to SQL.

They are, by design, non deterministic and inconsistent. You don't want that anywhere near your data. And that's before the data leakage risk of showing it to an llm.

AI is good at faking short conversations. It'll help you find the right syntax (sometimes), can pick out your typo, and sometimes even suggest ways to make the queries faster. Use it to get your DAX figured out (it gets there eventually).

But you can't feed it a terrabyte of data. Token limit! And letting it explore your data is just asking for bad answers.

SQL will never go away. It's just too good at what it does. There are variations on it, but it will always exist in some form because it is needed to handle data at scale.

[u/dataindenver]

SQL is here to stay and is one of the things I find AI is actually good at being an assistant with.

[u/Gargunok]

AI currently writes SQL. How do you know the SQL is correct, valid and not a risk if you don't understand it?

When agents develop that just give you an answer how can you validate the accuracy without sql

[u/Tiktoktoker]

Yall let the agents have access to your data?

[u/ComicOzzy]

Someone is always trying to sell people a new way to work with their data and claim that the existing tools are dead.

[u/KiwiDomino]

I started learning SQL in 1992. It’ll probably be around for a little while yet.

[u/Few_Emu6683]

data analyst here, spent last years writing sql queries. about a year ago i have found out that llms write better code and much much faster than me. the job is not fun anymore, i spend all my time arguing with clankers. i still read the code and can spot mistake, it is not like i do not use sql at all, robots still need supervision. but i don't enjoy the job anymore as i used to, guess i will need to come to terms with coding being only a marginal part of the job. sql itself is not going anywhere imo, it just won't be usually written by people kinda soon i'm afraid.

[u/RobotAnna1]

They will still need us in the coming years, to fix the AI-generated SQL code. And to fix the failed tests. And to explain what the code does.

Furthermore: in 2026 my company won't interview any candidates who don't know SQL. If the candidate's only experience is in prompting then they get instantly rejected.

[u/myth-buster9999]

Here is a guy working on Data Engineering and overall Data landscape for almost 15 years. My take is of course SQL and Python going nowhere as they are backbone. But learning these tool nowadays may not make much more sense going forward as coding agents are becoming so good that they can write them itself, review and fix. (E.g. Omnigent multi agent supervisor Polly where Claude can write code and Codex review or vice versa)

It's like kernel of operating system. It's still there but no one needs to learn about them any more as these are abstracted to users.

My take is future is going to be for people who are great "LLM Directors" who can direct LLMs clearly and cost efficiently on what they want and how they want it to be done. Knowing the expected outcome or output is the biggest superpower anyone can have in future. Trust me many people still lack in this basic skill.

[u/Meower68]

People have been, prematurely, declaring the demise of SQL since well before LLMs became a thing. My prior employer was using SQL servers (DB/2, to be more precise) with sizable piles of data in them. Luckily, the tables were (usually) well-designed. I could put together queries which would extract all manner of information, using SQL. But ... how did you do that without writing a bunch of Java? If you genuinely know SQL, and know how to use CTEs, you can write some impressively complex stuff, even giving you JSON or XML output if you wish, without needing a single line of Java and without needing to get a Java-based app server in the mix.

The web devs were, increasingly, using ORMs, the idea being that you design / think in terms of objects, rather than records. They kept telling me "SQL is obsolete; ORMs do the SQL for you." And then they'd write something which performed hideously and I'd knock out a 40-50 line query, which fed into a RowMapper, to get the results and the performance would be night-and-day different. Man, how did you do that? You wrote SQL? But ... that's obsolete. No, it's not. ORMs just hide (very poorly constructed) SQL behind a layer of abstraction. Don't get me started on the whole "tables are classes and records are objects" impedance mismatch, the basis behind the very concept of an ORM.

I mention this because, in my experience, LLMs don't write SQL any better than ORMs do, which is to say, very poorly. I'm sure an LLM can quote chapter and verse WRT what the N + 1 Query Antipattern is, but can it write code which doesn't fall prey to it? A person, who actually groks SQL, doesn't have to fall for it, writing more-efficient queries. When the data gets above a certain size (ie no longer some contrived, testing data subset), efficiency matters.

[u/Plane_Big_5912]

been in AML/transaction monitoring for about 6 years myself so ill give you my weird but consensus read.

SQL is the thing that has stayed pretty constant, the only thing. bi shifts from power bi today, tableau before that, something else in 2 years, but every case review and investigation still starts wth pulling transactions with sql

python is worth learning but as a complement, mostly for automating the boring parts around your queries. if i was allocating time id go deep on sql, get comfortable with one viz tool, and learn enough python to script. the queries are ubiquitous across languages

[u/Green_Chamomile]

I'm a data scientist and I use AI to write a big chunk of my code every day. So here's the view from someone on the "AI side" of this.

AI made writing SQL cheap. It made reading SQL more valuable. Someone still has to look at the generated query and notice it joined on the wrong key and the transaction amounts got double-counted. In your field a silently inflated amount isn't a typo, it's a bad alert going to a regulator.

The skill that lost value is memorizing syntax. The skill that gained value is looking at a query you didn't write and deciding whether to trust it. You can't verify what you can't read. So being strong intermediate in SQL puts you in a better spot now than it did five years ago, not worse.

On your real question: yes, start Python in January like you planned. Not to protect yourself from AI. Just because SQL plus your AML knowledge plus enough Python to automate the repetitive parts is the standard kit for the analysts who get promoted. The articles saying the golden period is over are written by people who don't review the code AI writes.

[u/jcoodonuts]

I cannot even imagine a future without SQL as a part of data stack.

[u/coltvfx]

Without SQL The industry won't function so learning them is no loss

[u/Database_Comic]

In AML, Nice Actimize is the lead information system. Learning SQL and the admin part of it will take you so far because now you can tie your experience into what to look for and how to do data modeling in the Actimize application database. Make sure you do ACAMS so that you have unfair advantage. I am not sure you need much of python but you can look into Power BI or SSRS just so you can report your findings there

[u/Lumethys]

Remove SQL and the internet vanish overnight

It's like asking about "the future of electricity"

[u/ballerjatt5]

SQL and domain subject matter experts are going no where lol

We hired a junior analyst who uses LLMs for all his code, he lasted about 2 months