I'm not talking about the obviously ridiculous AI hallucinations. I'm talking about those answers that looked completely believable until someone actually checked the numbers.
Maybe it was a calculation, a misleading chart, or a metric that meant something entirely different from what the AI assumed. What happened, and how did you catch it?
what kind of checks and balances to you implement to make sure the numbers are accurate, at least the critical ones. Anomalies are easier to spot, but minor but important inaccuracies are tough to identify.
The Querri Library is where your data gets organized around the questions your business asks, so every answer comes from the same trusted, shared foundation.. The library learns your definitions, business context, and past analysis, so its answers are grounded in how your business actually works. And when it doesn’t know, it says so, instead of making things up.
There is no denying that we have come to rely on AI for the smallest of the things - ChatGPT, Claude, Gemini now have made it to the Maslow's hierarchy of needs. Besides these generic AI tools, what otherAI data tools you rely on everyday for your work?
Given all the AI tools out there today, what is one challenge with data that still remains unsolved? why do you think it hasn't/can't be solved easily.
Querri transforms how teams work with data, making it easy to connect, clean, analyze, and visualize - all in one place. With new integrations and interactive, drag-and-drop dashboards, anyone can now build automated workflows and shareable insights - no technical expertise required
Our What s your biggest data frustration? thread got way more love than I expected.
Reading through it, it hit me: everyone needs a place to rant about their data chaos - dirty spreadsheets, broken dashboards, wild analytics expectations.
So what if we created The Venting Room? A community where data people can share rants, memes, and maybe even fixes together.
