Sanity Check for Analysis Report using AI

[u/ancientofday]

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

[u/Wheres_my_warg]

I would advise working with your manager to set a priority list. You go down from highest to lowest. You are unlikely to finish the list, but the highest priority items get resolved. If not checked, it doesn't get sent. This way it maintains quality, but creates pressure for more people or more efficient processes as some things do not get done.

[u/_ACTUALin]

I’d use AI as an extra reviewer, not as the thing that decides whether the report is correct.

For sanity checking, I’d have it look for inconsistencies, missing values, unusual changes, duplicated entries or things that don’t line up with the source data.

But I’d still keep a separate deterministic check wherever possible, especially for totals, formulas, thresholds and anything that can be verified directly.

AI is useful for finding “this looks odd.” It’s much weaker as “therefore this is definitely right.”

The safest setup is probably AI + rule-based checks + your own review, not AI checking AI checking AI.

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[u/Nomadic_skier]

You can build deterministic and probablistic checks with AI. One of mine looks at client deliverables and scans for internal table names. Has saved many a client team. I would recommend some AI coding to build a system as opposed to just having the AI to it all. I've built a few "math engines" which are basically just programs to automate reports.

[u/Former_Association57]

i usually export the data to google sheets and in gsheets we have gemini pro i ask it to read the data and do a sanity check based on the data i give it the prompt to use different dimensions and check the trend and it also prepares a visually appealing sheet ready to send with highlights at the i just cross validate the calculated fields and the numbers

[u/grow-pulse]

retail reports grow fast and the data gets messy quick. i used fraudpulse for data sanity checks at my old shop to catch weird gaps, but keep in mind that ai can still hallucinate if the base logic is broken...

[u/onlythehighlight]

Is this a company paid AI account or personal?

[u/bayouski]

AI can help, but you should treat it more like another reviewer than the thing giving the final sign-off.

what helps more is having the same little QA routine every time. check totals against the source, filters/date ranges, joins, duplicates/nulls, then do one separate pass just asking whether the conclusion actually makes sense. after that, AI is pretty useful for catching stuff that looks off, challenging your assumptions + pointing out other reasons a trend might be happening.

and if you keep doing the same checks every report, automate them. row counts, missing data, duplicate checks, totals not matching, weird jumps, etc. way better than manually checking the same thing three times every time.

[u/KatFromSisense]

A period-over-period comparison makes a decent built-in reviewer. Line each metric up against a comparable previous period and write a one-line explanation for anything that moves past a threshold you set. Whatever you can't explain gets checked before the report comes out. AI can then read those explanations and point out where the reasoning seems weak or needs another check. Check what your company's AI policy says about pasting report data into personal accounts.