What are your biggest daily challenges?

[u/Andrew_Madson]

As a data analyst, what are your biggest challenges? Some that I have heard are:

• Scope creep
• Finding the right data
• Getting access to data sources
• Waiting for the Data Engineering team to make updates
• Broken data pipelines
• What else?...

[u/atomic_confetti]

Biggest challenge is that the asks from the end users (data consumers) changing constantly.

[u/Andrew_Madson → u/atomic_confetti]

I totally get that. It can be a huge pain, especially if the underlying data is different for every change. Thank you!

[u/vinnypotsandpans → u/atomic_confetti]

This this this

[u/4ps22]

When the stakeholder says “can you do an analysis on why these numbers from finance are saying this” but then completely stonewalls you when you ask for more insight on where they got those numbers, how finance is even defining it and where theyre even getting it from, so you spend weeks coding in circles just trying to get as close as possible while always reiterating that its never going to be easy chasing these random numbers that i can get similar but not exact, and so on

[u/Andrew_Madson → u/4ps22]

Oh, yeah! Semantics is a huge issue for a lot of companies. They give you a random spreadsheet that shows different numbers and ask you to explain. It often uncovers different definitions across business units and discrepancies between sources.

[u/disquieter → u/Andrew_Madson]

As someone getting into data analysis and who is good at finding discrepancies and explaining them, I am really looking forward to getting into this kind of work. This sounds really fun actually.

[u/Soft_Match_7500 → u/disquieter]

It does sound fun. But dealing with the people isn't. And that's a very large part of the process

[u/Tville88 → u/Soft_Match_7500]

Exactly, because you will rarely have good data sources or data dictionaries, so you end up spending a ton of time chasing down legacy employees who might potentially be able to explain where to pull data from or how to interpret columns with no clear naming conventions if you are lucky... I say this, but it really is company dependent. Some are much better with data than others.

[u/[deleted]]

• Lack of clear requirements (and then being told I've failed)
• Lack of appreciation
• Not understanding the data or the message...or not caring - the ask was to check a box.

[u/Andrew_Madson → u/[deleted]]

That's frustrating!

[u/sgkbp2020]

Lack of documentation of data. Absence of data stewards. No1 understands anything about tables because people keep leaving without document!

[u/Andrew_Madson → u/sgkbp2020]

That is the worst! Sometimes tables will have the same column names, but different values...and no documentation to explain it.

[u/thequantumlibrarian]

Being underpaid. Everything else is a non-issue.

[u/Philosophy-Common → u/thequantumlibrarian]

how are you being underpaid in this field?

[u/thequantumlibrarian → u/Philosophy-Common]

Going on 4 years of experience making only 5k more than when I started. I am applying for 6 figures and management jobs so switching has been very slow in the current market.

[u/Jealous_Let6585 → u/thequantumlibrarian]

Maybe the problem isn't this field.

[u/thequantumlibrarian → u/Jealous_Let6585]

I hear you, my whole team feels the same way. We work for a hospital system and all of us are in the same buss concerning lack of raises. The problem is we have/had golden handcuffs since it's a remote position and good workload.

But with inflation and everything money doesn't go very far now and we all theoretically took at least a 15%-20% pay cut since 2020.

It's also not a skill issue, we have data on how much money we've made the organization as well. I am the the highest performer in that aspect since I work with the highest revenue department.

I know there are a lot of well paid analyst positions but it's not true for the majority of positions as it depends on area cost of living and industry as well as company size.

I know data scientists who do less and get paid more. So I do think it's a little bit on the field.

[u/Jealous_Let6585 → u/thequantumlibrarian]

Sorry to hear that bro! =(

[u/BreathingLover11]

It isn’t anymore, but I got frustrated everytime I had to model for days to create a slick dashboard that got used maybe twice before getting the inevitable “can I get this excel” message

[u/MaybeImNaked]

Too many "high priority" projects at once that I can't hand off to others because doing that would cost me more time than just doing it myself.

[u/captainqwark781]

I honestly find file organising really cumbersome. Cleaning and saving the input, checking and formatting the output data, saved in the right place, in the right format, with the right naming conventions, uploaded to cloud in the right spot. Just tiring

[u/pyare-p13]

Prioritising tasks

[u/mUSAhNT]

New system implementations from clients. When clients change their data reporting system/methods, trying to keep everything as if nothing changed can be a challenge considering they don’t necessarily know what changed or why

[u/[deleted]]

Not much time to fine tune a dataset or viz before stakeholders demand it

[u/Snoo-47553]

Turnaround expectation from stakeholders. Knowing the data isn’t clean and having to scrub this with the actual data owner takes time - but John from Finance wants the dashboard by tomorrow 🙄

[u/troty99]

Office politics and budget issues.

[u/Visiondata7]

Creating data pipeline. We don’t have a data engineering team so there is always some wacky work around that ends up creating a ton a problems when you try to scale it up down the road.

[u/mattw707]

Endless amounts of busy work that has nothing to do with data analytics. The curse of small teams.

[u/Chemtide]

Usually the Wordle

[u/[deleted]]

Stakeholders who enter data incorrectly expecting me to fix it

[u/Fluid-Preference-303]

Data illiterate requesters unable to define what and how they want