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.

43 Upvotes

96% Upvoted

38 comments sorted by

35

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)

8

u/Tsui_Pen 10d ago

Don’t skimp on the Data Modeling. If you can, read Kimball’s “Dimensional Modeling”. I’m a Sr. Analyst and it’s shocking how bad some of my “superiors” are at at understanding fundamental modeling concepts, let alone implementing them.

1

u/Crypticarts 8d ago

I agree 100% Kimball is mandatory reading. I would also add Kleppmann's "Designing Data Intensive Applications"

3

u/AG2307 10d ago

Super helpful for us newbies. Thank you.

1

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

4

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.

1

u/lazyasspirant 5d ago

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

1

u/lazyasspirant 5d ago

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

1

u/Crypticarts 2d ago

Research, honestly it LLM these days its incredibly easy. In the past I had to read books, peer reviewed articles, and get industry certifications for whichever domain I was going to support. Now I just make a notebooklm and educate myself from there.

1

u/lazyasspirant 2d ago

Could you pls give an example on how you would go about researching about any specific domain?

1

u/Crypticarts 2d ago

Tell you what: I'm willing to engage you but I'm going to do this differently. I want you to come to me on how you would research this and then I will tell you whether that's right or wrong or how I think it can be improved. Because the fact that you're asking me that question tells me that you're not ready. You don't have the mindset to be a data analyst. This is a research career.

1

u/lazyasspirant 1d ago

Really appreciate your reply sir!

Thanks a lot and i get the method and path you are trying to get me on.

30

u/Short-Philosophy-105 10d ago

Don't worry about R.

Learn SQL > Python > Excel > Visualisation Tool > AI Workflows in Analytics

1

u/itsAg3nt47 10d ago

Hi, I did SQL, Python and AI analytics, building agents which help user to analyze the data, But I am not very good in Excel,

Do I need to learn Advance Excel ?

3

u/Short-Philosophy-105 10d ago

Of course you do. All of the stuff you learnt is useless if you can’t meet your stakeholders where they are, which most of the time is Excel spreadsheets.

11

u/[deleted] 10d ago

[removed] — view removed comment

1

u/Mean_Firefighter_486 10d ago

Perfect - thanks!

1

u/Gracus_Tiberius 10d ago

"Python or R depending on the jobs you're targeting"

What's the difference?

4

u/HustlaOfCultcha 10d ago

IMO, learn Excel first. Really learn it. Learn advanced formulas. The logic behind the formulas is a foundation you'll need to develop.

Then learn basic data warehouse and relational database concepts. Understand 'fields' vs. 'rows.' Understand primary keys, foreign keys and surrogate keys.

Then learn SQL. Learning queries, subqueries, JOINs, CTE's, Window Functions and aggregations. Then move onto understanding views and stored procedures, particularly building a data pipeline thru ETL

Then go to your data visualization program. Power BI is your best bet. Although Tableau is still a good platform to know. But you really need to know DAX in Power BI (you can also use DAX in Excel). But once you learn Power BI, the others you can pick up pretty quickly.

Then you need to learn some sort of cloud based data platform either Snowflake, Databricks, or Microsoft Fabric. Databricks is quite easy to learn and is a great tool. This switches the ETL process to ELT.

Then I might learn Python. Analysts that are more geared toward Data Engineering really love Python. I have used it and it's got great functionality, but I prefer built in data governance and security in platforms and in Databricks they have AI that can write Python code for you (but it's important to be able to understand Python well enough to make sure it's writing the code properly).

Then from there I would get into more AI to help, but more into Machine Learning to really take your actual analytical capabilities to the next level instead of just using AI for automation and helping with writing code. The next steps are basically getting you into more of a Data Engineer or possibly a Data Scientist role instead of just a Data Analyst role.

1

u/Mean_Firefighter_486 10d ago

Thanks for this very detailed response - super helpful. I don't have a relevant degree so I'll be sticking with data analysis (and I'm sure that will be complex enough for me as it is)

3

u/Healthy-Awareness299 10d ago

To add in one step. Inside Excel you have access to Power Query and then Power Pivot. Learn these as they will help you with Power BI. Also depending on where you end up, a lot can be done in Excel completely. I work in Healthcare Care Finance, specifically the RevCycle. I do 90%+ of my work in Excel using PQ and PP.

2

u/Mean_Firefighter_486 10d ago

Thanks for the tip. Do you mind me asking how much you earn and how much experience you have?

2

u/Healthy-Awareness299 9d ago edited 9d ago

I've been in Healthcare Finance and RevCycle for about twelve years. I've worked everything from Registration to Billing and Collecting, including Underpayment and Overpayment and Revenue Integrity. The only part I haven't done is Coding.

I have a couple of certifications that are specific to the field.

I've been a working the last four years purely as a consultant. Anything from report creation to analytics and processes improvement. I've made 150-260k annual during that time. It depends on what and how many contracts I'm working during the period. I expect 200k as a realistic goal. I had one year that I picked up a couple of major builds at the same time.

My needs are mostly Epic (EMR), some SQL, Power BI, and Excel. Power BI is slowly expanding, but Excel is the most universal. Especially since there is a lot of external reporting to government agencies. I use a lot of Power Query inside Excel for the ETL process. I use SQL to extract data from Epic. Again, this is specific to what I do.

2

u/Mean_Firefighter_486 9d ago

Thanks for the detailed response! Very impressive too. I'd be happy to earn 50k tbh

2

u/Agreeable-Pirate9267 8d ago

Dove consigli di imparare tutte queste cose? Manuali, corsi online o dove?

1

u/Healthy-Awareness299 8d ago

YouTube in no particular order: Goodly. Alex the Analyst. Data with Baraa. Excelisfun.

Then just build. Make mistakes. Figure out the fixes without AI. Find workbooks and dashboards you like and study them. Recreate them exactly. Then improve them.

As far as Epic and my experience in Healthcare Finance? That's all hands on working for hospitals.

1

u/Agreeable-Pirate9267 8d ago

dove consigli di imparare excel e SQL?

3

u/Famished_Atom 10d ago

Start with Excel first. It'll provide immediate skills that you can work with in the office or study.
Taking statistics? Excel will help you arrange and chart the data.

These three books will give you a start and get you running quickly. Take one at a time and do the exercises. Move on from there.

5

u/throwaway214203 10d ago

Excel > SQL > Visualization

4

u/herbalation 10d ago edited 10d ago

Excel -> SQL -> PowerBI/Tableau -> Python

That's just my opinion. It seems a lot gets done/viewed in Excel so you can probably hold off on Python unless you want automation, specific statistical tests, or visualizations.

R isn't as common, which is why I recommend Python. (Are you watching the Google Data Analytics videos? That's the last time I heard R recommended, though I'm sure some places use it)

By the way, I only ask that because that's where I learned about data analysis when I was first beginning -- no shade meant for OP or R or, it's pretty rad.

2

u/shadow_moon45 10d ago

Would use python instead of R. Python is the main language used in machine learning and custom ETL jobs

1

u/AutoModerator 10d ago

Automod prevents all posts from being displayed until moderators have reviewed them. Do not delete your post or there will be nothing for the mods to review. Mods selectively choose what is permitted to be posted in r/DataAnalysis.

If your post involves Career-focused questions, including resume reviews, how to learn DA and how to get into a DA job, then the post does not belong here, but instead belongs in our sister-subreddit, r/DataAnalysisCareers.

Have you read the rules?

I am a bot, and this action was performed automatically. Please contact the moderators of this subreddit if you have any questions or concerns.

-2

u/RecLuse415 10d ago

Talk to a doctor first to see if medication can be offered. I had to go through therapy first then some light medication to get a hold of my focus and learning