Opinion

Data is getting too complicated for Excel to keep up

Towards Data Science
Python is taking over what used to be Excel-dominated terrains. Image generated with Leonardo AI

Spreadsheets are bogging us down. For all the reliance on Excel in the corporate world, clinging to it is like trying to run a Formula 1 race in a broken-down car. Sure, it is familiar and widespread. And, to be fair, it does work for many tasks ranging from simple data extraction in investment banking to fairly complex insurance pricing models.

Nevertheless, when it comes to data with thousands of entries, often interrelated tables and complex clusters, using Excel can get downright dangerous when it comes to managing today’s complex data. Take this: Excel’s row limit is infamous, leading to high-profile disasters like the UK’s COVID-19 data mishap, where thousands of test results were missed due to Excel’s constraints.

Or consider the untold hours wasted double-checking manual entries, only to end up with reports that can still fall victim to human error. The truth is that Excel is dead weight when you are dealing with data analysis from a certain level of complexity onwards.

In an age where even simple consumer apps handle complex data faster and with more precision, why are we still dealing with the…