Research shows that 88% of spreadsheets have some sort of error in them and that approximately 50% of spreadsheet models in use operationally in large businesses have material defects. Financial modeling agency F1F9 put together a book “The Dirty Dozen: 12 Modeling Horror Stories & Spreadsheet Disasters” and some of the spreadsheet blunders that have received publicity have negative impacts in the billions.
So, what about all of the cases that have gone unreported? Are you and your fellow analysts ready to make sure you don’t become #13?
How Exactly Can Dataiku Help?
If you work in a spreadsheet tool like Excel today, we have good news for you: You can go beyond the limits of spreadsheets onto new, exciting adventures in analytics, data science, and AI. Dataiku — the platform for Everyday AI — is as intuitive and robust as a spreadsheet (and then some). It allows you to do the complicated things you want to do with your data, but also you don't need to be an expert coder in order to accomplish.
You’re probably experiencing some of these pains working in spreadsheets:
- Row limits and cell character limits can’t handle big data.
- Slow load and processing times and “out of memory” errors on large files.
- Visibility and process documentation: It’s hard to reverse engineer someone else’s work or quality check their transformation steps after the fact (which leads to tricky handoffs if someone leaves or a new team member picks up the work).
- It’s hard to iterate on and modify sequences of operations without undoing all subsequent steps.
- Unless you’re a macro wizard, you probably find yourself repeating the same work over and over each time an analysis needs to be tweaked or refreshed.
If you want to know the key similarities and differences between spreadsheet tools and Dataiku, powerful visual recipes that make data prep and reporting a breeze, and how to go places your spreadsheets simply can’t follow, check out the video below (less than 25 minutes!) for a full rundown on how Dataiku eradicates the day-to-day pains mentioned above:
Spreadsheets Fall Short for the Enterprise
As we’ve seen, the only way that teams of today (i.e., analysts or other business people) will be able to truly collaborate on enterprise-grade data projects with complex datasets is by streamlining that work into one tool so everything — so data prep to modeling to MLOps and beyond — is visible in one place and there’s no need to toggle between tools. As a result, teams will be able to regain lost time, avoid duplicate work, and avoid the high-impact risks that can derive from data security problems or costly spreadsheet errors.