How Innovation is Changing the Analytics Landscape


Jen Underwood, Founder of Impact Analytix, LLC

Jen Underwood, founder of Impact Analytix, LLC, is a recognized analytics industry expert. She has a unique blend of product management, design and over 20 years of "hands-on" development of data warehouses, reporting, visualization and advanced analytics solutions. In addition to keeping a constant pulse on industry trends, she enjoys digging into oceans of data. Jen is honored to be an IBM Analytics Insider, SAS contributor, former Tableau Zen Master, and active analytics community member.

In the past, Jen has held worldwide product management roles at Microsoft and served as a technical lead for system implementation firms. She has launched new analytics products and turned around failed projects. Today she provides industry thought leadership, advisory, strategy, and market research.

Jen has a Bachelor of Business Administration - Marketing, Cum Laude from the University of Wisconsin, Milwaukee and a post-graduate certificate in Computer Science - Data Mining from the University of California, San Diego.

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Re: Computing power
  • 12/29/2017 3:01:48 PM
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Seth, the self-healing machine concept is an intriguing one to me as well. But I can't thing it to be beyond the anticipated probable failures. The knowledge base needed to address any failure in the system must exist first. The machine cannot go beyond the limits of the architecture.

Re: Computing power
  • 12/28/2017 8:54:01 AM
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The idea of "self-healing" is an intriquing one, I think of how the cloud has in one sense allowed Google's Chromebook and Chrome systems to "heal" glitches and make improvement to those computers and devices without intervvention by the user, and presumably AI and automated systems are doing much of the work behind the scenes making it true that it all done "to eliminate or reduce non-value-added activities to increase overall value," as noted.

Re: Computing power
  • 12/28/2017 2:06:55 AM
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I think it's true that humans are the thing that technology needs to be backward compatible for.   Maybe A.I.s will one day lament and complain "Why do we still need to interface with humans?"  Until we start modifying ourselves with that technology. 

On another subject, what I would like to learn more about is what the article referred to as self-healing in analytics.  I've heard that in machines repairing themselves, like a p.c. 

Re: Computing power
  • 12/27/2017 1:03:49 PM
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Seth, when the advances outpace the human labor force, the only way to maintain any degree of connectivity is making the newest and fastest technology backward compatible. Obviously that hampers the race to higher efficiency and appears to defeat the purpose of implementation. Hence the quagmire facing major industries and government agencies.

Re: Computing power
  • 12/26/2017 12:50:47 AM
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@ Lyndon,  I think techonolgy is of course advancing more rapdily.  However, when the technology has to interface with the average employee or consumers directly, it probally isn't advancing as fast as we like. 

Re: Computing power
  • 12/23/2017 7:19:14 PM
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I agree. It is a lot to think about. Do we let machines become more capable or at some point do we restrain them?

Re: Computing power
  • 12/23/2017 4:32:00 PM
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Jen Underwood writes

We live in an incredible era of extremely fast, disruptive innovation. Globalization, accelerated technology change, infinite cloud scale, ubiquitous connectivity, and an Internet of smart things is enabling a fourth industrial revolution, the digital transformation. The challenges data and analytics professionals are facing right now are not technology related. The challenges are related to adapting to constant change and keeping up with the frenetic pace of innovation to remain relevant.

I can imagine the day coming soon when the pace of innovation is faster than the ability of humans to keep up at all. Only AI machines will be able to keep up. The machines will then face the problem of the pace of innovation technology accelerating faster than the pace of the capability of AI technology at a given point in time to keep up.

Faster, more agile machines could be developed, but if the pace accelerates past a certain breakpoint, there could be an accumulation of outdated technological hardware, i.e., debris, lost to obsolescence and disruption in the accelerating race. This could raise benefit:cost issues.

There are probably multiple outcomes and solutions to this hypothetical situation. It might be useful to start pondering them.

 

Computing power
  • 12/21/2017 5:09:15 PM
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I think one of the biggest drivers has been the advance of computing powwer. Most smart phones have more power than supercomputers of just a few years ago. This enables much more complicated and visual analytics solutions. The more power, the simpler it seems.

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