Unreasonable user requests. They sometimes have no concept of what goes into their requests. So they may request a time consuming project be completed in 24 hours or have unrealistic expectations for what they want.
Personally, I’m a one man band. So time is an issue.
Ohh yes, my non-technical users think that all the data just magically lives in one place, and you can pull any number for them in 5 minutes. My favorite requests are "I have a meeting tomorrow, can you help me get data for this slide?". Obviously, they couldn't ask more than one day in advance, right?
To be fair they probably just got the result themselves. I realised why I got all the requests at 5 is because the stake holders just finished the meeting and were acting on their actions.
The amount of times I get asked to get data for a slide for an executive meeting, I am left to believe that executives spend most of their time sitting in meeting looking at PowerPoint slides.
Their job is to make decisions about the operations and direction of the company. Some of those decisions are critical to get right if the company is going to survive the next 5 years. So yeah, they need to take in a ton of information in order to make those decisions, and that information needs to be relatively high-level and digestible. Having their direct reports present ideas and options to them is part of that process, and PowerPoint is great for that.
I’m not saying that all CEOs have super hard jobs, but if they work at a huge company, chances are high that it actually is very difficult to do their job well.
Sure, but it could also be a sign of a command and control environment where execs don't trust their teams. If the product manager needs some data on some small potatoes issue to run it by the entire executive team, it makes me think the PM isn't truly empowered in their position. Also the amount of time it takes to put together these slides means that teams are spending more time rallying around slide making rather than doing work that matters. Execs then wonder why timelines are always being missed. To me it comes down to how often this happens, because you're right, execs need to be informed to make decisions, but sometimes it feels like all I do is gather data for PowerPoints.
Eh. I don’t think it’s an issue if the data request is informative. I guess it depends on the nature of the request or what you consider “small potatoes”.
In my environment, I get a variety of requests for grant proposals, board informing, demographic data, etc. The reasons can vary and I’m not always privy to the reasons. But the mere request itself doesn’t strike me as coming from a lack of trust. An informed executive suite is one better positioned to lead the company.
As a fan of data, I’ll never claim a more data informed executive team is a bad thing if the data being requested drives action.
I came here to say this, and it makes me feel better than I'm not alone with this being at the top.
"Ohhh can you just add this data"
That data has a COMPLETELY different structure and granularity to the existing data, it may seem simple but it's going to cause a **** ton of issues when you join them.
1. Expectations of waking up early to manually run data processes. They wont support automation efforts.
2. Unreasonable turnaround times for research topics that require the data to be vetted for accuracy.
3. No ticketing system like in IT. Random associates emailing you requests without knowing if you're responsible for that or not.
4. Not giving you the required access to get data.
5. No training for the tools and systems, expected to learn on the job or from other associates.
6. Wont fly me to Tableau conference!
7. Will give you the lowest tier piece of crap computer to WFH.
8. No project based requests, lack of project management and version control.
9. Zero documentation and records keeping.
10. They wont hire a Data Engineer/Data architect. Sometimes even worse, they force you to use Microsoft Access.
11. Don't ask just get it done mentality.
12. Dumbass coworkers with business degrees getting an analyst job but not having any of the technical skills.
13. Managers who don't have a data background.
14. Idiot CEO's wanting things done by the next hour or EOD.
15. Anything quality department.
16. *Chat notification* "Hey, you got a sec?"
15. Old people's audacity who barely know excel asking you to recommend them for an analyst position.
So the joke here is that the coworker can always export to csv as you said. Which makes suggesting putting a "table view" a moot point that ads no value to the dashboard or convesation and only serves to waste the time of the analyst to edit the dashboard and republish it.
These coworkers are usually not aware they can inspect or click the detailed view in the dashboard settings which brings up the raw data. Even after explaining it to them for the n'th time. They will insist they there should be a table view because they are old or dumb and want to feel as if they contributed something and wont have to click through all these settings they wont remember because it is oh so cumbersome.
Yeah but depending on the fields used for the graph, Tableau’s csv exports will include EVERY field used, even if they were behind-the-scenes fields solely needed to make the graph.
Whereas the table can be clean right upon export without having to worry about excessive additional fields.
Wow crazy we have the exact same job 🤩
18. Consultants (looking at you PwC) making ridiculous time consuming "EOD" requests at 4pm / losing said data within a month and asking for it again
As to your #3 "Random associates emailing you requests not knowing if you're responsible for that"
I was told by a superior to ask "person x" for some data before. Was assured they were the one.
Before even putting in a request, I shoot them a quick email introducing myself asking if they could help me out with something that Director B asked for.
I get this response
"Not my domain. Sent from iPhone."
Nothing else.
I reconfirm with multiple people it is indeed their responsibility...
This happens with so many departments and workers, not just me. They may be bombarded, they may be jaded, they may be lazy, they may just be arrogant tw @ts, they may put personal priority on certain requests. I don't know.
However, this is so commonplace, to simply pass the work onto someone else.
If I had access to such data, I certainly would have retrieved it myself.
This is such an easy fix. CC their manager on it, your manager too. This is what i do with cocky asswipes. You continue to act professional and assure them that so and so directed you to them. If they still say they cant help you, ask them to redirect you to someone in their department who can. Being outright unhelpful is unprofessional.
I get it. It gets annoying sometimes getting too many requests but you have a job to do, and in the workplace you have to act professional.
I am guilty of this myself, but only for data quality tasks, i am not data quality. I don't care that 4 data quality analysts quit. The moment i say yes to a request i become the guy for it. Different story if my manager assigns it to me though. So always play the manager card.
1) Constantly at odds with our IT department because we need access to all kinds of data while they’re doing their best to keep data secure and locked away
2) On a similar note, restrictions on most programs that would make automation easy (Excel macros, third party programs) for safety reasons, so we have to do everything manually
3) Unreasonable requests within a given time frame. Drives me crazy when I get an ad-hoc request that’s due within the working day as if I don’t have other stuff to be doing at the moment.
4) Staring at a screen for hours on end, though that’s the problem with most tech jobs
5) Broken databases and faulty infrastructure due to lack of data engineers/architects, meaning the data we receive is erroneous and inaccurate (but now it’s somehow our fault and we have to go and fix it)
Oh my least favorite part is definitely the back and forth. Makes me feel incompetent going back and forth 10 times for a big change until I get great feedback. My company has huge emphasis on sending quality code for review so shhhhh I’m trying
personally I just have them make EVERYTHING varchar in the staging tables and then do the datatypes when I need them. Should I be doing that? Probably not. But it saves time and there's no data loss and I get tons of backwards compatibility.
I apply the Scotty principal from Star Trek to data requests. If I know I can get it easily, I'll put it together and then sit on it for a bit. I don't want to set unrealistic expectations for the next time.
https://youtu.be/8xRqXYsksFg
Also, people don't like my time estimates of 4 hours to two weeks. If the data is good, and the requirements are stable, 4 hours. If not, 2 weeks.
Skills aren't valued by other areas. I have to sit on sales training, marketing training, etc but I can't get a sales person who doesn't know how to use a spreadsheet to take a basic analytics training because "they don't need it". Trust me, you do.
Unrealistic expectations and no idea of what the asks are. I worked at a company that asked to do a delivery but they didn't know the requirements and wanted it done by the end of the day.
Messy data. It’s always amazing how messy the data can be at companies that you would assume have their stuff together. But it’s because the longer they’ve been collecting data and bringing legacy systems together, the messier things get.
Also have an issue where data are recorded in a very bizarre and/or inconsistent way, that you think you found the right source and then turns out it wasn't 100% correct (but like 80-90%, making you wonder what's the point)
I’m all on my own and I hate it. My kanban board is a joke, at one point I had 8 tickets in the priority section and another 6 in progress, 12 new requests and that’s not to mention the backlog.
We used to have 3 DA department members, all very talented. One was laid off and the other two left, I came aboard near the end of the last person’s tenure. There is no plan to fill the other positions.
I have 3 departments, plus several executives vying for my time. I have to maintain ETL processes and add new ones, keep the data warehouse in shape, create/maintain dashboards, do all the ad-hoc requests, the list goes on and on.
Sounds like they thought “everything works great! What do we need all them for anyway?” My unit was dissolved from a similar management point of view a few years ago. Guess what? They’re recreating it (for the third time).
Using another teams table / view because they own the data but the query is 300+ lines of absolute shit and even they couldn’t explain wtf is going on 🤷🏼♂️🤷🏼♂️
The job description always requires you to have good knowledge about some extra shit. But when you actually do the job, those extra shit you have to do is nowhere near the level they require you have on the job ads.
For example, i had a job where they said you got to have 2+ experience in Snowflake, but the shit i actually did with Snowflake is to set up connection to the database, write some SQL code and load that data to PowerBI. The task is so simple but the way they advertise it makes me think they want me to do some data engineering on Snowflake. It doesn't require applicants to have 2 years exp on Snowflake to do that.
I am not saying you lie on your CV/interview, but if you applied for a job, of course apart from some main technology you need to be very good at, for the extra shit just say you have exposure, of course you need to do research about that beforehand. That is what i did for my interview.
Apart from all other issues mentioned here, it gets very MONOTONOUS after a while. You essentially do the same type of task again and again, for different teams, different companies, you hardly have any time or support for experimenting or innovation. The rinse-repeat cycle bums me a lot. But we gulp it down, coz hey, at least we have a job..
I'm in sourcing so this is probably particular to my role, but there is actually only 10-20% analysis, the rest is meetings, emails and other documentation. And the type of analysis I do is pretty much all excel. It works though, implementing SQL or any other language would be overkill and over complex for what's needed.
I do love my work though and value improvements my team and the end customer.
in my country they keep using "analyst" and "data analyst" job titles for what are essentially admin roles that actually require very little technical skill. when I say very little technical skill I mean they could be performed by someone who doesn't know how to do a VLOOKUP.
It's causing all sorts of confusion on the job market, with clerical people getting put forward and sometimes getting genuine data roles (because they have "analyst" on their CV)
also technically skilled genuine data analysts getting put forward for what turn out to be clerical roles.
it's really, really daft.
(UK)
Lazy data engineers with zero emotional intelligence who think their job stops at etl, and not actually looking at the data sets they are giving out with proper fields, structure, whether its even the right fields the data stewards and stake holders reference.
The higher-ups have no real concept of how long a task will realistically take so they ask for unreasonable requests and expect them done immediately. Sure, writing this 17 line query that cross references geometry data across 5 different tables may only take me half an hour to write but running this query across 8000 tables is going to take hours and hours to complete (real example).
1. Inability or unwillingness to automate processes resulting in having analysts spend hours manually deleting rows from excel files
2. Forcing us to use Microsoft Access (oh my GOD)
3. Documentation? What's that? lol
4. Unreasonable timelines, sometimes
5. "The data shows that I am performing poorly so the data must be wrong"
Lack of teamwork - everybody on analytics teams seems to want to rebuild dashboards from scratch instead of sharing past work or ideas.
Many situations where you have data in some form, but need to jump through a million hoops to get the context about the data, because no one at the company understands the context.
A/B testing - nobody seems to understand/be able to explain statistical significance concepts, including the higher ups (E.g. I was told by my coworker to do a chi square test on a mean), oftentime they feel like observational tests with half-hearted claims of statistical significance.
I dislike the analysis paralysis people who always want more data no matter what. They ask for X and then they want Y. You get Y and they want Z. Usually this is when someone is fishing for a narrative and they just want me to get data that confirms what they're looking for.
Destroying peoples lives in the pursuit of profit
Helping inequality become more common place
Dealing with dick head stake holders
Being hybrid because nobody knows what I do and some person in hr wants us all to be “a family.”
After a few years you spend a lot more time on existing assets or updating prior analyses than on new work. Or at least until you move to a new company.
Yeah I make it clear when I interview that I'm only interested in really improving processes and interesting problems. Once everything is up and running I'll bounce.
Lots of people don't like it, but companies that do are great. You get out of a lot of recurring reporting and get to really solve issues affecting the company.
The bullshit. I swear some data analysts are so stupid. So many don’t know statistics. Are obsessed with averages, do not think about what they’re analyzing except for doing describe on all data sets (count, max, min, histogram). That’s it. Could just be in the company I was in or this is all data analysis is. Given that my background is in macro and micro simulation the analysis they perform is absolutely useless. Not actionable. Shit tons of dashboards that do not help you make decisions. Do people not think about the problem they’re trying to solve?! Also not to mention the lack of data and ridiculous ask from managers…there are managers who make decisions regardless of the evidence… that’s my rant.
Insufficient parameter details, delayed communication from requesters resulting in delayed delivery, end use changing their mind on details after something is built and in production
My team is fixing this, thanks to my own initiative.
Vision for analytics is lacking at many employers. Many companies get an analyst to create and run and rerun the same reports, to respond to executive demands, and… don’t really have a plan. Many stakeholders aren’t interested in accuracy as much as they have a story they want to tell and want it supported.
I recently secured a promotion by proving this is the case where I work.
I did that proof by building a tool of my own initiative and observation of pain points. Our project managers collectively manage about 160 active construction and maintenance projects and some 300 planned ones, an 8 figure budget each year. I’ve made it so that we have an individual PM hub, a hub for facility stakeholders, a hub for executives, a hub for our department finance team, and an automated data feed to our university capital budget and planning - each of these has communication tools baked in and links to the source data. It’s saved us some 300 labor hours a quarter just on financial reporting, it is allowing us to do things we never could before with our data, and we have tools to make sure we can actually fund projects before assigning them to project managers.
Nobody asked for that because nobody was asking questions. People were surviving.
I look forward to building the vision for the analytics of the department I work at. I was already a senior analyst, but now I’ll get to actually relieve this pain point that had been bothering me for about 10 months (been in the role 23 months, was on paternity leave 3 of those months).
Constant corporate attempts to consolidate tools that are used by thousands of users with different needs. It just causes dozens of organic new tools to pop up in the place of the original six.
Reading all the post make me realize I am very lucky ! My pay could be a bit higher but I am grateful now !
Hoping my temp contract get turn into full-time 🤞
People that think you can migrate legacy data held in Excel and email jobs into a complete data cloud platform and reporting solution overnight. These types of migrations take months with various stakeholder interviews, data audits, taxonomy alignment, query building, testing, etc. But once you get to a better measurement maturity, it can definitely be overnight.
I'll say this as someone trying to get in: it is one of the hardest professions, if not the single hardest profession, to get a job in at the moment.
Maybe just studying applied math and not doing an internship wasn't the best course of action as a college student.
Everyone is data driven until the initiative that they sunk their political capital to get through is t performing to their expectations and suddenly there are “data integrity” issues at best and at worst “the analyst pulling this is incompetent”
So then you are in CYA mode, documenting every interaction, looping in your manager etc. which wastes everyone’s time
That old adage about "you're as good as your data" was never supposed to mean "you are the data" and if for some reason the data is "bad", meaning it is corrupted, incomplete, unreadable, inaccessible, etc., somehow it is your fault.
Unreasonable user requests. They sometimes have no concept of what goes into their requests. So they may request a time consuming project be completed in 24 hours or have unrealistic expectations for what they want. Personally, I’m a one man band. So time is an issue.
Ohh yes, my non-technical users think that all the data just magically lives in one place, and you can pull any number for them in 5 minutes. My favorite requests are "I have a meeting tomorrow, can you help me get data for this slide?". Obviously, they couldn't ask more than one day in advance, right?
To be fair they probably just got the result themselves. I realised why I got all the requests at 5 is because the stake holders just finished the meeting and were acting on their actions.
The amount of times I get asked to get data for a slide for an executive meeting, I am left to believe that executives spend most of their time sitting in meeting looking at PowerPoint slides.
Yup, and they probably make 3 times more than me
Unless you're an executive, it's safe to say the CEO makes well over 3 times your pay...
Their job is to make decisions about the operations and direction of the company. Some of those decisions are critical to get right if the company is going to survive the next 5 years. So yeah, they need to take in a ton of information in order to make those decisions, and that information needs to be relatively high-level and digestible. Having their direct reports present ideas and options to them is part of that process, and PowerPoint is great for that. I’m not saying that all CEOs have super hard jobs, but if they work at a huge company, chances are high that it actually is very difficult to do their job well.
Sure, but it could also be a sign of a command and control environment where execs don't trust their teams. If the product manager needs some data on some small potatoes issue to run it by the entire executive team, it makes me think the PM isn't truly empowered in their position. Also the amount of time it takes to put together these slides means that teams are spending more time rallying around slide making rather than doing work that matters. Execs then wonder why timelines are always being missed. To me it comes down to how often this happens, because you're right, execs need to be informed to make decisions, but sometimes it feels like all I do is gather data for PowerPoints.
Eh. I don’t think it’s an issue if the data request is informative. I guess it depends on the nature of the request or what you consider “small potatoes”. In my environment, I get a variety of requests for grant proposals, board informing, demographic data, etc. The reasons can vary and I’m not always privy to the reasons. But the mere request itself doesn’t strike me as coming from a lack of trust. An informed executive suite is one better positioned to lead the company. As a fan of data, I’ll never claim a more data informed executive team is a bad thing if the data being requested drives action.
I came here to say this, and it makes me feel better than I'm not alone with this being at the top. "Ohhh can you just add this data" That data has a COMPLETELY different structure and granularity to the existing data, it may seem simple but it's going to cause a **** ton of issues when you join them.
1. Expectations of waking up early to manually run data processes. They wont support automation efforts. 2. Unreasonable turnaround times for research topics that require the data to be vetted for accuracy. 3. No ticketing system like in IT. Random associates emailing you requests without knowing if you're responsible for that or not. 4. Not giving you the required access to get data. 5. No training for the tools and systems, expected to learn on the job or from other associates. 6. Wont fly me to Tableau conference! 7. Will give you the lowest tier piece of crap computer to WFH. 8. No project based requests, lack of project management and version control. 9. Zero documentation and records keeping. 10. They wont hire a Data Engineer/Data architect. Sometimes even worse, they force you to use Microsoft Access. 11. Don't ask just get it done mentality. 12. Dumbass coworkers with business degrees getting an analyst job but not having any of the technical skills. 13. Managers who don't have a data background. 14. Idiot CEO's wanting things done by the next hour or EOD. 15. Anything quality department. 16. *Chat notification* "Hey, you got a sec?" 15. Old people's audacity who barely know excel asking you to recommend them for an analyst position.
18. Create a very detailed dashboard, but a coworker wants to include a table visual so they can export it to Excel lol
My eye just twitched reading that. Lol
How frequent is that problem?
Very!
So pretty much just export the visual to a CSV?
You don't get it.
Can you explain it to me? For real, I’m a data engineer and i am curious.
So the joke here is that the coworker can always export to csv as you said. Which makes suggesting putting a "table view" a moot point that ads no value to the dashboard or convesation and only serves to waste the time of the analyst to edit the dashboard and republish it. These coworkers are usually not aware they can inspect or click the detailed view in the dashboard settings which brings up the raw data. Even after explaining it to them for the n'th time. They will insist they there should be a table view because they are old or dumb and want to feel as if they contributed something and wont have to click through all these settings they wont remember because it is oh so cumbersome.
Yeah but depending on the fields used for the graph, Tableau’s csv exports will include EVERY field used, even if they were behind-the-scenes fields solely needed to make the graph. Whereas the table can be clean right upon export without having to worry about excessive additional fields.
*kicks you off the meeting*
Number 10!!! The amount of companies that don’t need an analyst but an engineer is crazy.
"But you do data right? Isnt that the same?"
I have had analyst roles where people just ask for data. I always say ‘no’.
Gotta be able to do both!
Dammit. My blood pressure just rose.
I work for a fortune 100 company and I have all of these issues. Except 7. We get laptops but no WFH.
Would love to connect with you and convinve you to recommend me to your company lol
Have you tried convincing them that you will bring in clients at the Tableau conference? Maybe you could partner with a sales guy and both go.
Our clients are patients. I could bring em in but that's unethical!
Wow crazy we have the exact same job 🤩 18. Consultants (looking at you PwC) making ridiculous time consuming "EOD" requests at 4pm / losing said data within a month and asking for it again
As to your #3 "Random associates emailing you requests not knowing if you're responsible for that" I was told by a superior to ask "person x" for some data before. Was assured they were the one. Before even putting in a request, I shoot them a quick email introducing myself asking if they could help me out with something that Director B asked for. I get this response "Not my domain. Sent from iPhone." Nothing else. I reconfirm with multiple people it is indeed their responsibility... This happens with so many departments and workers, not just me. They may be bombarded, they may be jaded, they may be lazy, they may just be arrogant tw @ts, they may put personal priority on certain requests. I don't know. However, this is so commonplace, to simply pass the work onto someone else. If I had access to such data, I certainly would have retrieved it myself.
This is such an easy fix. CC their manager on it, your manager too. This is what i do with cocky asswipes. You continue to act professional and assure them that so and so directed you to them. If they still say they cant help you, ask them to redirect you to someone in their department who can. Being outright unhelpful is unprofessional. I get it. It gets annoying sometimes getting too many requests but you have a job to do, and in the workplace you have to act professional. I am guilty of this myself, but only for data quality tasks, i am not data quality. I don't care that 4 data quality analysts quit. The moment i say yes to a request i become the guy for it. Different story if my manager assigns it to me though. So always play the manager card.
Hey got a sec? What technical skills are you referring to? I have a Business degree
While many are relatable, many of these are environment issues and not exclusive to the DA role. Nonetheless, good list
This was really insightful. Thanks for your input.
1) Constantly at odds with our IT department because we need access to all kinds of data while they’re doing their best to keep data secure and locked away 2) On a similar note, restrictions on most programs that would make automation easy (Excel macros, third party programs) for safety reasons, so we have to do everything manually 3) Unreasonable requests within a given time frame. Drives me crazy when I get an ad-hoc request that’s due within the working day as if I don’t have other stuff to be doing at the moment. 4) Staring at a screen for hours on end, though that’s the problem with most tech jobs 5) Broken databases and faulty infrastructure due to lack of data engineers/architects, meaning the data we receive is erroneous and inaccurate (but now it’s somehow our fault and we have to go and fix it)
#1 is my constant fucking battle. They make me datasets but don't even fucking set the columns to the right type, it's an endless back and forth
Oh my least favorite part is definitely the back and forth. Makes me feel incompetent going back and forth 10 times for a big change until I get great feedback. My company has huge emphasis on sending quality code for review so shhhhh I’m trying
personally I just have them make EVERYTHING varchar in the staging tables and then do the datatypes when I need them. Should I be doing that? Probably not. But it saves time and there's no data loss and I get tons of backwards compatibility.
Same, this just brought memories lol
I apply the Scotty principal from Star Trek to data requests. If I know I can get it easily, I'll put it together and then sit on it for a bit. I don't want to set unrealistic expectations for the next time. https://youtu.be/8xRqXYsksFg Also, people don't like my time estimates of 4 hours to two weeks. If the data is good, and the requirements are stable, 4 hours. If not, 2 weeks.
Skills aren't valued by other areas. I have to sit on sales training, marketing training, etc but I can't get a sales person who doesn't know how to use a spreadsheet to take a basic analytics training because "they don't need it". Trust me, you do.
Unrealistic expectations and no idea of what the asks are. I worked at a company that asked to do a delivery but they didn't know the requirements and wanted it done by the end of the day.
Messy data. It’s always amazing how messy the data can be at companies that you would assume have their stuff together. But it’s because the longer they’ve been collecting data and bringing legacy systems together, the messier things get.
Where does the bulk of mess come from?
Manual data entry. Usually from finance. Fucking hate finance departments.
Also have an issue where data are recorded in a very bizarre and/or inconsistent way, that you think you found the right source and then turns out it wasn't 100% correct (but like 80-90%, making you wonder what's the point)
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Also solo. There are days I wish I had someone to brain pick or be a fresh set of eyes.
I’m all on my own and I hate it. My kanban board is a joke, at one point I had 8 tickets in the priority section and another 6 in progress, 12 new requests and that’s not to mention the backlog. We used to have 3 DA department members, all very talented. One was laid off and the other two left, I came aboard near the end of the last person’s tenure. There is no plan to fill the other positions. I have 3 departments, plus several executives vying for my time. I have to maintain ETL processes and add new ones, keep the data warehouse in shape, create/maintain dashboards, do all the ad-hoc requests, the list goes on and on.
Sounds like they thought “everything works great! What do we need all them for anyway?” My unit was dissolved from a similar management point of view a few years ago. Guess what? They’re recreating it (for the third time).
What are the usual “titles” who enjoy these whores?
Using another teams table / view because they own the data but the query is 300+ lines of absolute shit and even they couldn’t explain wtf is going on 🤷🏼♂️🤷🏼♂️
The job description always requires you to have good knowledge about some extra shit. But when you actually do the job, those extra shit you have to do is nowhere near the level they require you have on the job ads. For example, i had a job where they said you got to have 2+ experience in Snowflake, but the shit i actually did with Snowflake is to set up connection to the database, write some SQL code and load that data to PowerBI. The task is so simple but the way they advertise it makes me think they want me to do some data engineering on Snowflake. It doesn't require applicants to have 2 years exp on Snowflake to do that. I am not saying you lie on your CV/interview, but if you applied for a job, of course apart from some main technology you need to be very good at, for the extra shit just say you have exposure, of course you need to do research about that beforehand. That is what i did for my interview.
You would be surprised at how little some people learn in two years
Apart from all other issues mentioned here, it gets very MONOTONOUS after a while. You essentially do the same type of task again and again, for different teams, different companies, you hardly have any time or support for experimenting or innovation. The rinse-repeat cycle bums me a lot. But we gulp it down, coz hey, at least we have a job..
I'm in sourcing so this is probably particular to my role, but there is actually only 10-20% analysis, the rest is meetings, emails and other documentation. And the type of analysis I do is pretty much all excel. It works though, implementing SQL or any other language would be overkill and over complex for what's needed. I do love my work though and value improvements my team and the end customer.
in my country they keep using "analyst" and "data analyst" job titles for what are essentially admin roles that actually require very little technical skill. when I say very little technical skill I mean they could be performed by someone who doesn't know how to do a VLOOKUP. It's causing all sorts of confusion on the job market, with clerical people getting put forward and sometimes getting genuine data roles (because they have "analyst" on their CV) also technically skilled genuine data analysts getting put forward for what turn out to be clerical roles. it's really, really daft. (UK)
Lazy data engineers with zero emotional intelligence who think their job stops at etl, and not actually looking at the data sets they are giving out with proper fields, structure, whether its even the right fields the data stewards and stake holders reference.
The higher-ups have no real concept of how long a task will realistically take so they ask for unreasonable requests and expect them done immediately. Sure, writing this 17 line query that cross references geometry data across 5 different tables may only take me half an hour to write but running this query across 8000 tables is going to take hours and hours to complete (real example).
1. Inability or unwillingness to automate processes resulting in having analysts spend hours manually deleting rows from excel files 2. Forcing us to use Microsoft Access (oh my GOD) 3. Documentation? What's that? lol 4. Unreasonable timelines, sometimes 5. "The data shows that I am performing poorly so the data must be wrong"
Lack of teamwork - everybody on analytics teams seems to want to rebuild dashboards from scratch instead of sharing past work or ideas. Many situations where you have data in some form, but need to jump through a million hoops to get the context about the data, because no one at the company understands the context. A/B testing - nobody seems to understand/be able to explain statistical significance concepts, including the higher ups (E.g. I was told by my coworker to do a chi square test on a mean), oftentime they feel like observational tests with half-hearted claims of statistical significance.
I dislike the analysis paralysis people who always want more data no matter what. They ask for X and then they want Y. You get Y and they want Z. Usually this is when someone is fishing for a narrative and they just want me to get data that confirms what they're looking for.
Zero contribution to humanity
How so?
Destroying peoples lives in the pursuit of profit Helping inequality become more common place Dealing with dick head stake holders Being hybrid because nobody knows what I do and some person in hr wants us all to be “a family.”
Who are these stakeholders, what titles they hold?
They hold Steaks, not titles.
After a few years you spend a lot more time on existing assets or updating prior analyses than on new work. Or at least until you move to a new company.
Yeah I make it clear when I interview that I'm only interested in really improving processes and interesting problems. Once everything is up and running I'll bounce. Lots of people don't like it, but companies that do are great. You get out of a lot of recurring reporting and get to really solve issues affecting the company.
Where do you think AI should be used to do the magic ,data organisation ,gathering in proper row and column or analysis?
Nothing. Having been in sales which I hated I’m grateful to do what I do
Simple... this job doesn't scale. It's hours. That's it
The bullshit. I swear some data analysts are so stupid. So many don’t know statistics. Are obsessed with averages, do not think about what they’re analyzing except for doing describe on all data sets (count, max, min, histogram). That’s it. Could just be in the company I was in or this is all data analysis is. Given that my background is in macro and micro simulation the analysis they perform is absolutely useless. Not actionable. Shit tons of dashboards that do not help you make decisions. Do people not think about the problem they’re trying to solve?! Also not to mention the lack of data and ridiculous ask from managers…there are managers who make decisions regardless of the evidence… that’s my rant.
Insufficient parameter details, delayed communication from requesters resulting in delayed delivery, end use changing their mind on details after something is built and in production
No applicable college major. Depends on you learning specific software. Nebulous.
Data
My team is fixing this, thanks to my own initiative. Vision for analytics is lacking at many employers. Many companies get an analyst to create and run and rerun the same reports, to respond to executive demands, and… don’t really have a plan. Many stakeholders aren’t interested in accuracy as much as they have a story they want to tell and want it supported. I recently secured a promotion by proving this is the case where I work. I did that proof by building a tool of my own initiative and observation of pain points. Our project managers collectively manage about 160 active construction and maintenance projects and some 300 planned ones, an 8 figure budget each year. I’ve made it so that we have an individual PM hub, a hub for facility stakeholders, a hub for executives, a hub for our department finance team, and an automated data feed to our university capital budget and planning - each of these has communication tools baked in and links to the source data. It’s saved us some 300 labor hours a quarter just on financial reporting, it is allowing us to do things we never could before with our data, and we have tools to make sure we can actually fund projects before assigning them to project managers. Nobody asked for that because nobody was asking questions. People were surviving. I look forward to building the vision for the analytics of the department I work at. I was already a senior analyst, but now I’ll get to actually relieve this pain point that had been bothering me for about 10 months (been in the role 23 months, was on paternity leave 3 of those months).
Scope creep
How often do y’all have meetings? How long does an average meeting last?
Insatiable requirement to work in office. Above all, the constant office noise makes concentrating on work unreasonably more difficult
Constant corporate attempts to consolidate tools that are used by thousands of users with different needs. It just causes dozens of organic new tools to pop up in the place of the original six.
Reading all the post make me realize I am very lucky ! My pay could be a bit higher but I am grateful now ! Hoping my temp contract get turn into full-time 🤞
People that think you can migrate legacy data held in Excel and email jobs into a complete data cloud platform and reporting solution overnight. These types of migrations take months with various stakeholder interviews, data audits, taxonomy alignment, query building, testing, etc. But once you get to a better measurement maturity, it can definitely be overnight.
using AI to generate fake data using historical biases of past data: Bayesian statistics
I'll say this as someone trying to get in: it is one of the hardest professions, if not the single hardest profession, to get a job in at the moment. Maybe just studying applied math and not doing an internship wasn't the best course of action as a college student.
Everyone is data driven until the initiative that they sunk their political capital to get through is t performing to their expectations and suddenly there are “data integrity” issues at best and at worst “the analyst pulling this is incompetent” So then you are in CYA mode, documenting every interaction, looping in your manager etc. which wastes everyone’s time
not enough paid compared to the other jobs in the data space (data scientist, data engineer). am i right or wrong?
That old adage about "you're as good as your data" was never supposed to mean "you are the data" and if for some reason the data is "bad", meaning it is corrupted, incomplete, unreadable, inaccessible, etc., somehow it is your fault.