Salesforce’s Tableau held its user conference in Las Vegas this week, where it made several announcements designed to improve performance and usability. It also announced a ChatGPT version, Tableau GPT, and Tableau Pulse, analytics personalized to user needs.
I saw the demos and heard the keynotes from my perch near Boston, and I’ve decided to let others go into the detail of, from what I saw, were some very nice analysis and visualization tools. You could even call them next generation and not be wrong.
In lieu of product specifics, I suggest we look at how the industry is positioning Tableau and products like it, usually focusing on the idea of data. It baffles me why the industry is so hung up on data, and the conference was a prime example.
I’ve been in this business for over 40 years, and while everything about the industry has changed many times, our notion of data hasn’t, and that’s puzzling. Of course, data is essential to everything we do, but our concentration on it has exceeded the concept’s staying power to the point that it may be holding us back.
Shifting Focus From Data to Information
Back in the day, data was everything. Our systems exceeded their storage capacities regularly, and we stored data in flat files (look it up!), which were cumbersome resource hogs.
The relational database management system came along just in time and made manipulating data easier. Still, except for the very largest businesses that used mainframes, we only captured and stored hundreds or perhaps thousands of megabytes.
Early RDBMS systems were designed to serve up data to users, who would then turn it into information in their minds to use for decision-making. But here’s the thing: today’s CRM systems (along with most back-office systems) process data into information so users can consume it in real time.
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We make better and more in-depth decisions with today’s information, which should make us all very happy. So why are we still calling it data when it’s information we seek and consume? You might think this is quibbling over semantics, and I admit it sounds like it, but this inaccuracy goes deeper.
The words we use determine the ideas we can have. If we persist in using data when we mean information, we might be closing off potential solutions without even realizing it.
An amateur uses data to mean everything from an item number to a sales projection and asks questions like, what data do I need to understand my business? But a manager asks, what information do I need to see into and improve my business? While the amateur is looking back, the manager is forward-thinking, and there’s the rub.
Bridging the Power of Information Gap
What’s maddening is that at the Tableau Conference, they said data and then demonstrated information. Some amateurs watching this will have trouble with the transition, and some won’t. Many will be frustrated that their approach to data does not approximate the demonstration of the power of information, and the disconnect will mystify them.
It’s our job to educate the markets about our technologies, and in doing so, everyone progresses. But when we deliberately use data to mean information, we’re dumbing down and appealing to the common denominator.
My point is that progress gets made at the margins, not in the safe center.
I hate to seem like I am picking on Tableau, especially for something non-product related, and also, because the data/information divide is so well entrenched, it will take a lot to change things.
But if progress really is made at the margins, then it behooves all of us to go there. I know there are still many appropriate uses of data, like in data lake or CDP. Nonetheless, the sophistication of those technologies only further proves that guys like Tableau are dealing with information. That’s what we should embrace.
