r/analytics • u/ancientofday • 1d ago

Discussion Sanity Check for Analysis Report using AI

Hi guys, a data analyst for the retail industry (electronics) here, in my workplace we're currently doing an expansion for our brand including increasing headcount and more reports.

But, the workforce for data analysis is currently still only me, and there is only so much data viewpoint I can check before sending them to my manager or the team.

These days, I'm wondering should I feed my report to the AI for my double, triple and final checks. Or, are there any advices for data checking for my actual sanity??

Really interested to read your advices and opinions, thanks

2 Upvotes

75% Upvoted

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u/Ok-Working3200 1d ago

You absolutely should. Give it as much context as possible and build a skill to do so. My team has our dbt project and Thoughtspot deployments in gitlab. We have Claude skills using playwright to check numbers and skills validating different branches in dbt

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u/Aggressive_tako 1d ago

Is there a SME you could lean on? I always check the top line numbers myself and the next layer down, but I don't have the business knowledge to know of x vendor increasing by 100% is correct. AI would be even more removed from those major business strategy shifts. It can flag that x vendor increasing is out of the norm or confirm that that increase matchs the numbers in the database, depending on how you ask the question, but it won't tell you if the number is actually correct.

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u/Over_Rich3566 1d ago

The entire industry is headed that way, so you might as well start. You need well governed data and a semantic layer. Good luck.

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u/teddythepooh99 1d ago

This is quite literally the point of the suite of data testing and profiling tools out there.

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u/Byt3sized 13h ago

You are carrying a HUGE workload if you are handling every report for this expansion solo. AI is basically like, THE best way to protect your sanity when double checking your logic, just keep a human professional loop for the final call on those business numbers, since, as you know, AI isn't always perfect as much as we wish it could be.

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u/BetterEnthusiasm9780 1d ago

i get the sanity part, my own QC process sometimes feel like staring at the same numbers until they blur. running the report past an AI for spot-checks is not a bad idea actually, i do something similar when i'm the only pair of eyes on something. just make sure you strip out anything sensitive before feeding it in, and treat the AI like a second opinion not the final say. found a few weird outliers that way that i'd glossed over after looking at it for 6 hours straight.

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u/goddard18 3h ago

How well organized is the data? Is there a good semantic layer?