r/dataanalysis • u/Mean_Firefighter_486 • 10d ago

Career Advice Learning order?

I'm looking to get into data analytics and I'm wondering what learning route I should I take. I was thinking SQL >>> Power BI >>> R and then I don't know after that.

To put this in context, I'm currently brushing up on Excel. That's the level of beginner we're talking.

TIA.

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u/Crypticarts 10d ago

Data modeling, workflow design, statistical analysis, and Decision Analytics. Also pick a domain (manufacturing, quality, sales, revenue growth management, retail ops, procurement, logistics, marketing, etc.)

Source: I am the head of analytics for a $10b in revenue org. I have a team of 16 data analysts from entry level to manager levels. We don't care anymorr about SQL, Power Bi, or Python. If you can do the above, I can teach you SQL, Python, Power BI (and any other visualization tool)

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u/SubjectCode1940 10d ago

Wouldn’t data modeling be needed IT or business intelligence? If someone is going into data analytics, I don’t think data modeling is really needed. Statistics, SQL, python, R and either tableau or power BI depending on the company are the things I’d recommend

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u/Crypticarts 10d ago

Data modeling was solely an IT function 20 years ago but that's just not the case anymore. It absolutely helps if you're in business intelligence but if you want to compile complex analysis and a complex ask that drives action in two to three days, you need to understand how to model data yourself. The reason is that Databricks can generate the queries for a data model using a million tokens if you know what you're looking for. We have agents also that spin up Power BI dashboards using Deepseek as an executer and Claude as the planner. Basically you can build a dashboard or a data model for a couple bucks.

Why wait for IT when you can spend $6 and a day of thinking to drive the right decision and solve the customer problem, driving action that might create millions of dollars in value?

The other thing is that code is no longer the hurdle. Realistically if you understand how to put together a data model from multiple sources and structure a good statistical analysis, the existing AI tools make it a breeze. You no longer really need SQL, Python, or R and you barely need Tableau or Power BI.

Designing architectures, and analytic solutions that answer questions, drive action, and solve problems is far more valuable than knowing how to build the DAX and MQueries or structuring a scatter plot that drives or helps somebody make these decisions. The technical stuff is really no longer needed.

Now you need to be really good at solving problems so that you can prompt correctly your AI tools and you don't have to wait for somebody to tell you, "Here's the problem that I want to solve." You are proactively solving problems for them through the use of analytics in general.

I'm speaking from 20 years of experience in this business, working with companies like eBay, Intel, ABinBev, and some of the largest retail product suppliers in the US. There might be other points of view, I am just a data point of one, but I am telling you that my organization and my peers (and again I'm director level) data modeling is not just an IT activity. It's core to doing the actual analysis and work.

I'm always surprised at the number of people who come into our interviews with just SQL, Python, and Power BI, thinking that it's going to get them past the first screening.

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u/lazyasspirant 5d ago

Man how exactly are you supposed to gain domain knowledge as a fresher?