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Are there RPA use cases in data work?
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Are there RPA use cases in data work?
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I feel like there’s a way to do both in parallel if you explain what you have found and the scope of the QA issues, but it will depend on your situation. You cannot report on wrong numbers but is it all data sources? And what is the scale of discrepancy in each source? If it’s not every source then maybe reporting for the affected sources can be handled manually versus in the database that you are usually expected to pull it from. Then you can work with the account leader to get your data integrity issues resolved. If they don’t go for that then just do what they say but keep bringing up internally the discrepancies with your boss and the team and they can make their own beds if they want to
This!
Is there an alternative “bridge” solution that you can use before the long term? Plot it out into a roadmap. Give them something to show you can do it, in the meantime work on the backend and tell them how much time you need. You need a roadmap.
It’s okay to tell them to wait, but you’ll need to compromise with what they can get today vs tomorrow, what needs to be done, and how much time you need.
Also, I’m the only analytics person in the team, but there are other analytics people scattered in different teams throughout the org. I honestly don’t know that we will get budget for an analyst, but we’ll see.
I believe I need to spend more time working with the BI team and developers right now than marketing reporting.
Can you provide analysis/ insights that back-up your story? Most folks are familiar with GIGO. I completely agree - need a good understanding of the data, sources, reliability well before the desire to make it pretty. This will be an uphill battle, but build the story and make the pitch. It sounds like a massive overhaul or at least investment is needed. Make the case.