I had a thought a while back: perhaps what marketers really want isn’t a fancy dashboard, or a supersized “Big Data” appliance. Instead, perhaps they would rather a simple way to come up with the answers to their burning business questions using whatever data they could get hold of. I have called this idea the “Analytics Selfie” (which will probably be the subject of my next book, as well).
But over the last week there have been rumors of the appearance of at least two new analytics offerings that are designed to do the same thing – answer your questions in language you understand. In case you’re wondering, you don’t need to be an analyst to pose the questions or run the analysis, because the platforms will do that for you. All you have to do is ask the question and load your data up into the application, and the answers await you, so they say.
According to a recent article in Business Insider, IBM is about to release an analytics application that answers your business questions, just “like magic”; the platform is called IBM Watson Analytics. Also, on October 15, Salesforce will release what is rumored to be an “Analytics Cloud” at the upcoming Dreamforce conference. What drives these new “Delphic oracle” analytics platform offerings from IBM and Salesforce?
Business users and their needs.
Most business users don’t know how to work with “Big Data”. In fact, many of them don’t even know what to do with simpler Web and social analytics data, which are much less ‘oceans of raw data’. There aren’t enough data scientists to pose and answer the questions businesses need to know about. Also, there are few organizations that can afford to hire top quality data scientists, or deploy them to get the most bang for the buck. As a result, the next evolution of analytics will be the ascendance of smart platforms that clean and converge the various data sets for users, whilst guiding and answering their questions.
I know this sounds strange, but in the next evolution of Convergence Analytics, the “Analytics Oracle”, could end up cutting many data scientists and convergence analysts out of the picture. This directly contradicts the McKinsey group’s prediction of a shortage of data scientists for the foreseeable future.
That’s not so far-fetched, considering analytics applications have become progressively more intelligent and aligned to basic business tasks that are connected to specific industries. Consequently, the analytics part of the offering becomes invisible, thereby letting users concentrate on their highly specialized business tasks, instead of the analytics data.
In fact, when the new “Analytics Oracles” become popular, the current business focus on promoting and producing more and more data scientists may turn out to be yet another “bubble”. After all, we are no strangers to bubbles, having lived through various financial, investment and technology bubbles over the last decade or so. And we certainly have room for more “bubbles” to form.
Considering the complexity and fragmentation of various analytics platforms, caused by emerging digital medias that are largely bootstrapped and then acquired once they became profitable, it’s no wonder Salesforce, Oracle, Adobe, Apple and IBM have been buying them. They then merge the data and reporting from those platforms into the various clouds we have been hearing so much about.
Finally, if the new data oracles are meant to put powerful analytics in the hands of every business user, that alone, could revolutionize our businesses and our society.
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