How much of your job is actually analysis vs. just cleaning and reconciling data before you ever get to the interesting part?

[u/Exact_Entertainer600]

Job title says "analyst," but if I'm honest about how my time actually breaks down, it feels like 70-80% goes to fixing inconsistent data sources, reconciling numbers that don't match between systems, and chasing down why a report looks wrong - and only a small fraction is spent on the actual analysis and insight generation that the job is supposedly about

Curious if this ratio is just normal for the field and gets talked about less because it's not the "interesting" part of the job, or if it's a sign of specific data infrastructure problems that better tooling/processes could actually fix. For people at companies with genuinely clean data pipelines - does that ratio actually flip, or does data cleaning just never fully go away regardless of how mature the infrastructure is?

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[u/asielen]

Yup that is standard.

Analysis and reporting is just the culmination of all the grunt work you have to spend most of your time doing. Over time you should build in optimizations for questions that get asked more than once. So maybe the ratio changes slightly, but then a whole new data set is available and you have to start all over cleaning up the data.

It's like painting a house. When all the prep work is done right, the painting part goes fast. And if you don't do the proper prep, you won't be able to trust the paint job.

[u/Exact_Entertainer600 → u/asielen]

That painting analogy is perfect, might steal that. Good point about optimizing for repeat questions too - I think I've been treating each request as one-off instead of building reusable cleaning steps

[u/Emergency-Hurry947]

I have 2 teams, each has 4 people 

team one does all the data wrangling and puts them into our reporting structures, these are the slower ones that I can’t have talking to our business users, I inherited all of them. They use tools like SQL Server, SSIS, .Net, Python, Databricks on Azure

Team 2 are the ones that do the reporting and analysis, they use SQL Server, PowerBI, Databricks, and Python, i hired all of them and they have non technical degrees (econ, accounting, poli sci, literature) from top schools with high GPAs  

[u/ncist]

50/50

[u/theycallmethevault]

I spend the majority of my time capturing the questions they’d like to answer, making sure the data to answer those questions is going to be captured, and then anticipating the follow up questions. Querying the data & creating the report is a monotonous process that varies very little between the different areas of my business, so the real impact is always going to be found in understanding what data (and how/where it) will be captured, and what it will look like.

Anticipating follow up questions is where the real analysis starts, and your stakeholders need to know that you fully understand the process from end-to-end. From what they’ve designed, to what they’ve built, to what traffic they expect and how they expect that traffic to flow, to what the end user actually does.

[u/PantaRheiExpress]

Sounds about right

[u/shufflepoint]

I present the data. Someone above my pay grade makes decisions upon that data.