Predictions for 2014, Round 1: Big Data, Data Discovery, InfoApps
in big data, Business Intelligence, data discovery, InfoApps, Predictions, Self-service, Big Data
Happy almost-new-year! You know what that means: prediction time.
Information Builders has seven predictions for 2014. I'll start with three here, and we'll post the rest next week. [UPDATED: Here.]
1. The term “Big Data” will get smaller, but data volumes will continue to go up.
Don't get me wrong: Big Data isn't going away. But the term "Big Data" will come to have less and less meaning as we get used to dealing with data in ways that we didn't before. We'll see fewer articles in Forbes about it. We'll see fewer philosophical arguments about what it is. We'll see fewer "Big Data projects" -- not that it was ever clear those were in the first place.
When I was a lad of ten, my dad -- who had worked in computers since the late sixties -- told me that he knew computers would change the world when Random Access Memory dropped below a million bucks a megabyte. Back then, "Big Data" was anything that you put into a computer. Normal data was in a filing cabinet. You only put data into a computer if you could extract more value from it somehow.
We're undergoing a similar transformation now. Two terabytes of data used to be a lot; now it gets stored on a hard drive you can buy at Target. "Big Data" is bigger, faster, and more varied, and has been tough to manage, by definition; in 2014, we'll have more, faster, and more varied data coming at us, but by the end of the year it's going to be Just Another Set of Data.
2. Isolated data discovery will hit the wall. Integrated data discovery will pick up steam.
Data discovery tools have made their mark on the industry over the past few years, driving up the revenues of data discovery companies and generating a ton of interest.
We're seeing signs, though, that people are becoming frustrated with standalone data discovery tools.
- People are showing up at meetings with completely different answers to questions.
- Nobody knows how the data is being manipulated to get the results, and there's no audit trail.
- The data's not from the right system, or contains errors, or isn't in a format that I can merge easily with other data.
- The tools have been promoted as a way to give more users access to information, but users have had a steep learning curve and sometimes make bad mistakes with them.
I don't know about you, but to me, that sounds like spreadmarts all over again. Standalone data discovery tools are causing the new Excel Hell. To prevent that, companies are going to be driven to integrate trusted data into their visualizations.
3. Analytic apps will be the biggest driver of user adoption in 2014.
I'm not talking about "analytic applications", which connotes pre-packaged data models and one-size-fits-all reporting packages that you buy from a vendor.
I'm talking apps. Like the kind of apps you have on your phone: small, interactive, business-focused, easy to use without training. Those are the kinds of apps that people want to use.
That's a big change. Analytic tools, such as the data discovery tools in prediction two, have been driving user adoption for a few years now. But, although people are seeing the Excel Hell-style disadvantages of tools, they still want to get their own answers quickly and with minimal IT involvement.
Information apps -- dare I say "InfoApps"? -- provide the level of interactivity needed to answer a bunch of important questions, but in the sandbox necessary to keep people from needing training or making errors. Fast, flexible results will start to drive adoption as tool usage becomes more difficult to justify.
I'm pretty confident in these three predictions. What do you think? Let us know here, or in the thread on Facebook.
By the way, I have another post coming about regifting our "Twelve Days of Jargon" from last year. See you in a little bit. :)