Will 2015 be the year of Big Data? Or was 2014 already that?

I just read the following interesting article on Big Data. That Big Data is here to stay is obvious, but the trick will be to use Big Data smartly . That is why I often speak of Smart Data instead of Big Data.

The data itself does not necessarily have to be 'Big'. Much more important is what you want to do with that data and how you want to interpret it. There has to be some purpose. Its quality and governance are also important.

We also often note that companies like to put the "big guns" on data. The market (software vendors and consultants) naturally likes to play into this. Often I also see that companies do not start this for fear of having a high project cost versus a lower benefit. I can promise you here and now that you can do 'Big Data' in a perfectly budget-friendly way. It is important to keep your objectives in mind with the desired benefits, to quantify them, and to build a big data project carefully, phase by phase. For many companies, it is enough to realize a large return and benefits with limited resources. You don't always have to go all the big data way.

The term was around much earlier, but in 2014 it was really put on the map: Big Data. Or rather, the promise of Big Data. All kinds of vendors promised even smarter techniques to pinpoint correlations in customer behavior. Gartner already put Data Science higher in its Hype Cycle in mid-2014, now that expectations around these solutions have become unrealistically high.

There were big announcements, for example from Salesforce, which launched its long-awaited Analytics Cloud this fall, along with a host of partners that themselves offer business intelligence (BI) solutions. The Russian search giant Yandex is establishing a B2B Big Data division in Amsterdam: applications could be in the areas of personalized recommendations on the Web, image and speech recognition, optimization of logistics issues, and natural language recognition.

IBM was also at the party again: the company wants to give a human face to Big Data with its supercomputer Watson. So you can ask Watson "normal questions," after which the system fishes out the right answer from the data haystack. Other companies like Marketo are also trying to make Big Data accessible.

One thing is certain: Big data is here to stay. The cost of storage is going down and so it is becoming more attractive to store and analyze data. The expected data explosion, meanwhile, is being driven primarily by a phenomenon like the "Internet of Things."

Demand for self-service analytics is high, noted market researcher IDC. Many companies are relying on data scientists to interpret Big Data, whereas, of course, salespeople and marketers should above all be able to do it themselves. And therein lies perhaps the biggest problem.

In the last two decades, the amount of customer data has multiplied. However, the company Selligy says that the majority of companies still do not have enough useful data at their disposal to do anything concrete with it.

Only 18 percent of organizations also have a holistic view of the customer. Companies are still silos that don't share information. While they are on top of it. Data and systems are not aligned, so companies lack insights into customer needs.

And thus threatens a phenomenon we have seen before: technology hollows out before need. Ronald Verschueren of Netmarketing UX Research wrote on Emerce in February, "The Big Data hype is a bit like a schoolyard fad: nobody organizes it, but suddenly it's there. And everyone is talking about it. If you want to stay in the game, you have to get involved. The result: a proliferation of related courses, workshops and books. The biggest driving force - with ever-expanding and unrealistic sales pitches - are often the software industry or consultants, who (try to) make big money from it.'

Data alone says nothing at all, Verschueren said. More of it says even less. 'Smart people who can analyze it in the right context and reliably, they have a right to speak.'

Gartner predicts that the blow is yet to come. Indeed, the fall down is "rapid. Techniques are being proposed before expertise in the field is well and truly available, and many of the developments are not mature enough. Consequently, Gartner believes that many solutions will disappear again.

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