Many of you reading this right now may be scratching your heads. What’s the difference?
Data are 1’s and 0’s in a computer hard drive. Analytics are the presentation of that data, which enables decision makers to process and act on it.
With all the hubbub recently around Big Data, I believe this subtle difference is often forgotten. Businesses fall in love with (and collectively pay billions of dollars for) the ability to collect and store petabytes of data describing every angle of their operations. But the ability to digest and visualize that data is just as valuable as the data itself. Without a front end, all of those 1’s and 0’s are worth less than the hard drive they’re stored on.
Take, for instance, a pretty manageable example of Big Data that most companies can relate to: a Salesforce.com CRM account. Contained therein is every communication the company’s Sales, Marketing, and Customer Service teams have ever had with an outside party, along with as many as hundreds of fields of information for each contact. This can include everything from basic information such as their title, to more niche data such as the vendors they currently use, all the way down to the prospect’s mother’s maiden name and the color of their underwear. As a rule of thumb, most companies assume the more information they keep, the better.
But it isn’t always obvious to Salesforce which fields will be important to the company, and in what way. As a result, Salesforce’s out-of-the-box analytics aren’t all that great. If you believe a certain field is going to indicate a good or bad prospect, you’re going to need to build out a report or chart to validate this.
And if you aren’t making decisions based on this data, why bother keeping it at all?
All too often, companies go to great lengths to amass huge amounts of data, but wrongly take for granted that they’ll be able to draw meaningful conclusions from it. All of that ‘valuable’ data just ends up gathering dust while the company goes about its business. It’s true that the more data you have, the more valuable it is. But more data is also harder it to digest. It isn’t going to analyze itself.
Front-end analytics, while less technically challenging (and therefore less sexy to many tech people), is an underappreciated hurdle standing in the way of the Big Data revolution. That’s why I love companies like Chartbeat and Geckoboard, who understand that the presentation of data is just as important as the data itself.
Over the next decade, as the amount of data created continues to explode, I expect the demand for capable front end systems to follow closely behind.