What does data democratization really mean?
It's not enough to give users the data if they don't have the levers to use it.
The goal of enabling every person in your organization to leverage all its information is often called data democratization.
This is often interpreted as giving everyone access permissions on the central analytics database. In other words, the absence of explicit restrictions.
But imagine if when you went to vote, the ballot was in a padlocked box next to a set of lock picks. Would you consider that democracy? No one’s stopping you from picking the lock and getting to that ballot.
The fact is that most people in your organization can’t write SQL queries, have forgotten most of anything they learned about statistics, and aren’t familiar enough with the particulars of those datasets to interpret anything they find.
There’s no question that an organization will benefit from more individuals learning data science. But expecting everyone to do that would be no different from expecting all voters to learn how to pick locks.
Data democratization shouldn’t just be the passive act of removing restrictions. If you want everyone in your organization to benefit from data and make data-driven decisions, you need to actively find ways to get the right forms of data to the right users, and connect it to their levers.