8 years, 6 months ago

Big data fetishes: social and mobile – Active Information

This week, I wrote about data fetishes on Active Information. Excerpt:

“On the Big Data front, I’m intrigued by the potential of fast, wide and deep data processing to solve hard problems, learn from outliers and make informed, data-driven decisions.

And, as my clients will attest, I advocate instrumenting everything as a means to discover true customer, business and systems behaviors.

However, I don’t believe that all data has equal value. Nor does all valuable data hold its value over time. Good data programs rely on context and include data weeding.

But, what about the data that should never, ever get in your attention? According to Wharton’s Peter Fader, the least valuable data is the noisiest in the Big Data space: social and mobile.”

Read the post: Big data fetishes: social and mobile – Input Output.
Related posts:

  1. Active Information: Big Data from left field; Big Data Rx
  2. Active Information: Data Scientists, Moneyball, Competitive Analytics & Big Data Definition
  3. Active Information: Reclaim the “I” in CIO, Big Data & Collective Intelligence
8 years, 11 months ago

Active Information: Streaming through Computational World, Changing change via experimentation platforms

My latest posts on the HPIO Active Information blog:

Streaming through a Computational World — (most popular post to date)

To take advantage of the computational world, or the nearer term internet of things, we need to infuse smarts throughout our data collection networks.  We need to employ up-front and intermediate filters, traffic cops, aggregators, pattern detectors, and intelligent agents.  We need to get over being data hoarders, and have the astuteness to leave data behind.

Busting cultural resistance via experimentation platforms — (changing change)

Culture, mistrust of the data, lack of interest. These very human factors are adoption barriers for 46% of the respondents. Yet, these barriers aren’t new. Nor, confined to big data and advanced analytics. To change a culture, you need to bring proof to the table.  And proof requires hands-on experimentation and real-world data. We need data to prove that we need data. How will we get that?

Related posts:

  1. Recent Active Information Writing: Crash-proof code, data lessons & infographics
  2. Active Information Writing
  3. Active Information: Reclaim the “I” in CIO, Big Data & Collective Intelligence