From data to insights to … intelligence

  • The value of big data has been constrained by the boundaries of the traditional paradigm of problem solving.

  • The challenge is to look beyond the usual data insights archetype and increase the focus on a third leg—big data intelligence.

As big data permeates more and more facets of both our business and personal lives, is its value being optimally realized?

Traditionally, the science of big data has been divided into two distinct components: data and insights. Big data scientists have become masters of finding the “needle in the haystack” in voluminous data sets and providing answers to confounding questions. Generally, if you can articulate the question (an art in and of itself), it is likely you’ll find a corresponding answer. Subsequently, you can take those answers, apply powerful but readily available analytics tools, and create insights that, if properly constructed, contribute to actionable findings.

Still, to this point, the value of big data has been constrained by the boundaries of mechanical conclusions—the traditional “ask a question/get an answer” paradigm of problem solving.

But what do you do with the insights created? This requires the kind of thought that extends beyond the rationality of computing. As with all things, the insights can be applied constructively or destructively, fairly or with prejudice, intelligently or frivolously. This is where the value of big data ultimately rests.

The challenge is to look beyond the traditional data and data insights archetype and increase the focus on a third leg that I call big data intelligence, or the second derivative of insights (insights of insights). The operative questions driving this leg of the model are, among others:

  • How can the value of insights be maximized?
  • How much of insights should be exploited before negative value return is observed?
  • Can insights be federated to create even greater intelligence?
  • How should insights be cataloged in the value-space-time dimensions?
  • What attributes should be ascribed to express the relative “good” that a given insight creates?

We’ve conquered the easy part of big data. Now, the challenge is to deploy its potential beyond answering questions, to drive toward intelligence in the way insights are applied. This is where the true value of big data will be realized.

Norbert Sluzewski Global Business Solutions Signature Client Group Strategic Advisory Services Director AT&T About Norbert