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SmartData Collective > Big Data > Organizational Knowledge: Hiding in Plain Sight
Big Data

Organizational Knowledge: Hiding in Plain Sight

MIKE20
MIKE20
3 Min Read
Organizational Knowledge: Hiding in Plain Sight
Illustration generated with FLUX.2 [klein 4B] via Cloudflare Workers AI.
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“I saw the angel in the marble and carved until I set him free.”

Contents
  • Overcoming Reluctance
  • Simon Says
  • Feedback

–Michelangelo

“I saw the angel in the marble and carved until I set him free.”

–Michelangelo

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Implications of the Organization of Data

The era of Big Data has arrived, yet relatively few organizations seem to recognize it. Platitudes from CXOs are all fine and dandy, but how many have invested in Hadoop or hired a data scientist? Not too many, in my view. (See “Much Hadoop About Nothing.”

Brass tacks: The hype around Big Data today is much greater than the reality–and it probably will be for some time.

This is unfortunate, as many organizations already have within their walls very valuable data that could be turned into information and knowledge with the right tools. Because of their unwillingness to adopt more contemporary Big Data and dataviz applications, though, that knowledge effectively hides in plain sight. The ROI question still paralyzes many CXOs afraid to jump into the abyss.

I know something about the notion of hiding in plain sight. It is one of the major themes of my favorite TV show, Breaking Bad.

Overcoming Reluctance

To some extent, I understand the reluctance surrounding Hadoop. After all, it’s a fundamentally different way of thinking about data, modeling, and schema. Most IT professionals are used to thinking about data in orderly and relational terms, with tables and JOIN statements. Those will the skills to work with this type of data are in short supply, at least for the time being. “Growing” data scientists and a new breed of IT professionals doesn’t happen overnight. The same thing happens with lawyers and doctors.

Overcoming stasis isn’t easy, especially in budget-conscious, risk-averse organizations. To that end, here are a few tips on getting started with Big Data:

  1. Don’t try to boil the ocean. Small wins can be huge, to paraphrase from the excellent book The Power of Habit: Why We Do What We Do in Life and Business.
  2. Communicate successes. Getting people to come to you is much easier than forcing them. The carrot is more effective than the stick.
  3. Under-promise and over-deliver.

Simon Says

Compared to a year ago, I have seen progress with respect to Big Data adoption. Increasingly, intelligent people and companies are doing more with new forms of data—and getting more out of it. As a result, data visualization has become a big deal. To paraphrase Michelangelo, they are starting to set the data free.

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