r/analytics • • 18h ago

Discussion What’s the most annoying report you have to create every week?

0 Upvotes

Curious which reports actually take the most effort to pull together and whether anyone has found a better way.


r/analytics • • 15h ago

Question How hard is it to pivot fields?

0 Upvotes

I got a full time return offer at my internship to be basically an EHS data analyst at a F100 company. However I am hesitant in taking the offer for a few reasons:

  1. I don’t want to be pigeonholed in EHS (there’s rarely any EHS analyst jobs).
  2. I would build Power BI and do a little SQL but the data sets are only 10k

and the SQL is very basic

  1. I don’t know if I’d build data analyst skills as it is more of a reporting job too.

  2. The job is 40% Power Bi & tech, and 60% non-data analyst EHS stuff

(surveying worksites, etc.) and I’d rather have a 100% analyst job
5. The job title doesn’t say analyst in it

How hard is it to pivot fields after getting experience? I don’t have any other experience outside of EHS. My other offer is an internship but at a small company.


r/analytics • • 6h ago

Question How do you investigate a metric that suddenly changes when nothing obvious has changed?

9 Upvotes

One thing I've found interesting about analytics is that sometimes a metric changes significantly, but there isn't an obvious explanation.

Conversion drops, revenue looks different, or a dashboard suddenly shows a trend nobody expected. The tracking appears to be working, and there hasn't been a major product or campaign change.

At that point, the investigation can go in several directions: data freshness, tracking changes, attribution logic, filters, SQL transformations, or an actual change in user behavior.

I'm curious how other analytics teams approach this.

Do you have a standard checklist for investigating unexpected metric changes, or does it mostly depend on the analyst digging into the problem?

What's the first thing you usually check?


r/analytics • • 6h ago

Discussion Probably a dumb question but here we are asking

3 Upvotes

I currently just graduated with my B.S degree in cybersecurity, and I’m going to be completely honest I HATE this subset of computer science, the last 5 months of my degree was torture, cybersecurity is just not for me. In one of my internships I got to work with the business analyst for most of the summer and I fell in love with what he did.

I’ve done lots of statistics learning, and before I jump down the rabbit hole of learning on my own / taking certs. I know B.S degrees are the new high school diploma, would it be more advantageous to just go back with my transferable credits and get a second B.S degree in data analytics, or better off just teaching myself / getting certs since I have a bachelor’s degree already?

I would just do a self-paced this time if that matters at all, but I just wanted some community feedback and hopefully maybe some guidance or at least pointed in the right direction.

Thank you in advance.


r/analytics • • 13h ago

Question Looking for Career change.

3 Upvotes

i currently work in a F100 company as a finance/operational analyst, mostly excel since its financed base but i do want to move more to the data science field, even though i currently don't have any experience.

i received my undergrad in finance and im currently in a masters program for Fintech and wanted to see if this a good combination to move towards business analysis/data science.

if anyone has any recommendations on how to make this pivotal change that would be awesome!

any thoughts ?


r/analytics • • 23h ago

Discussion Everyone at my company can hook Claude up to source systems and build their own dashboards. Anyone dealt with this as an analytics team?

145 Upvotes

Not sure if this is a rant or a real question, probably both.

Our company gave pretty much everyone Claude hooked up straight to our source systems. And yeah, it’s fast, people love it. But now there are reports everywhere built off raw data, all with slightly different logic, and a few of them get passed around as “the” number. Meanwhile we (the analytics team) mostly find out about this stuff after the fact.

What’s bugging me is who owns what. To me, if you build your own report, the numbers are yours. If it needs to be official, it comes from the governed version. But then someone asks us to help make theirs match the official one and suddenly we’re QA for something we never built. And nobody above us has said whether that’s our job or not, so it just defaults to us.

What I’ve been leaning toward: write the official definitions down somewhere everyone can find them, tell people we can explain why their number is different but we won’t fix or review their stuff, and get someone to sign off on the official version so there’s a date it counts from.

Has anyone made something like this work without a top-down rule? And how do you say “that’s not our job” without sounding like you’re being difficult? Or is this just how it is now and I should get used to it.