Four Challenges to Go Extract Insights from Big Data

According to the 5th annual Digital IQ Survey, consulting firm PwC found that 62 percent of respondents believe big data can give them a competitive advantage but that nearly 60 percent also believes that moving from data to insight is a major challenge.

The four challenges that stand between data and insights, according to PwC are:

  1. They’re blind to the importance of visualization.
  2. They’re investing more in gathering data than analyzing it.
  3. They’re facing a talent gap.
  4. They’re struggling with insufficient systems to rapidly process information.

A short elaboration by on the four data insights challenges are:

Businesses Blind to the Importance of Visualization
When it comes to actually deriving insight from the trove of data at most organizations’ disposal, visualization is fundamental. Visualization helps put data into context and bring business cases to life. In many cases, advanced visualization capabilities allow organizations to glean insights that would be impossible otherwise.

Investing More in Gathering Data than Analyzing It
Companies are investing significant amounts in gathering data, Rao and Halter say, but perhaps not enough to integrate, merge and analyze it: 32 percent of organizations have invested more than $1 million in gathering, storing and retrieving internal data, but only 26 percent have invested more than $1 million in analysis of internal data.

They’re Facing a Talent Gap
And that leads to the third big data barrier: the talent gap. As Rao and Halter note, it’s no secret that companies often lack talent in the skills necessary to interpret big data. Only 44 percent of PwC’s survey respondents said they have a sufficient pipeline of talent to undertake deep analysis of data, though top performers were more likely to feel they have a sufficient talent pipeline.

Struggling With Insufficient Systems to Rapidly Process Information
The fourth big data barrier is existing systems. Rao and Halter note that big data demands increased computing power to rapidly gather, store and analyze massive volumes of data. But many organizations doubt their ability to do so with their current systems. Forty-one percent of respondents in the Americas, 33 percent of respondents in Europe and 49 percent of respondents in Asia-Pacific said their systems can’t process large volumes of data from different sources. Even top performers mostly aligned with the pack with regard to confidence in their processing power.

Read the complete elaborations here.

The two that I can relate to are in the fields of the first and third challenge. Even simple data visualization can open up minds, contextualize and see new learnings. If you don’t have the budget to invest in data visualization tools, even Excel graphs help a lot.

I’ve elaborated on this challenge, I would advice to take a market researcher or more mathematical person in your team (depending on the type of data, structured and/or unstructered), to be really able to extract insights from data.

Do you agree with the four challenges or do you know of other ones?

Are you generating insights from big data?