Stephen E. Arnold: A Fresh Look at Big Data & Big Data (-) Human Factor (+) Transformation (+) RECAP

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Stephen E. Arnold
Stephen E. Arnold

A Fresh Look at Big Data

May 8, 2013

Next week I am doing an invited talk in London. My subject is search and Big Data. I will be digging into this notion in this month’s Honk newsletter and adding some business intelligence related comments at an Information Today conference in New York later this month. (I have chopped the number of talks I am giving this year because at my age air travel and the number of 20 somethings at certain programs makes me jumpy.)

I want to highlight one point in my upcoming London talk; namely, the financial challenge which companies face when they embrace Big Data and then want to search the information in the system and search the Big Data system’s outputs.

Click on Image to Enlarge
Click on Image to Enlarge

Notice that precision and recall has not improved significantly over the last 30 years. I anticipate that many search vendors will tell me that their systems deliver excellent precision and recall. I am not convinced. The data which I have reviewed show that over a period of 10 years most systems hit the 80 to 85 percent precision and recall level for content which is about a topic. Content collections composed of scientific, technical, and medical information where the terminology is reasonably constrained can do better. I have seen scores above 90 percent. However, for general collections, precision and recall has not been improving relative to the advances in other disciplines; for example, converting structured data outputs to fancy graphics.

 

I don’t want to squabble about precision and recall. The main point is that when an organization mashes Big Data with search, two curves must be considered. The first is the complexity curve. The idea is that search is a reasonably difficult system to implement in an effective manner. The addition of a Big Data system adds another complex task. When two complex tasks are undertaken at the same time, the costs go up.

Again I am not interested in identifying a particular Big Data or a particular search system. The main point is that when an organization rushes to embrace a blend of search and Big Data, costs are likely to be an issue.

There are four reasons:

First, the blend of search and Big Data is, in my opinion, new territory for most organizations. Search is “old news” and the cost of implementing a search system can be difficult to control. Even the Google Search Appliance imposes a price tag when deployed across a large corpus. Systems from enterprise giants like Dassault, Hewlett Packard, IBM, and Oracle can be substantial as well. Move these big company solutions in and expect to export fees.

Second, the technologies for search and Big Data are coming at information from two different directions. Search has been predicated on the user crafting a query to unlock whatever is in the index. Big Data is assumed to be too voluminous for anyone to “know” what’s in the content. The Big Data system discovers, reveals, shows, or performs some other function to find out what’s in the content.

Third, the computational processes for whacking away at Big Data can be resource intensive. The assumption or assertion that a system can process “all” or “everything” may be unfounded. Attempts to crunch Big Data may fail due to resource constraints or budgets.

Fourth, the fancy math which is easy to reference can be quite difficult to implement in a hybridized system. The reason is that multiple calculations exceed the computational capacity available for a task. Algorithms can be optimized which yields some benefits, but data scientists want to apply more sophisticated processes. As a result, the demand for computational resources in some situations continues to grow. At the same time, the volume of data to be processed grows as well. The result is that decisions have to be made to deliver “good enough” results. Usable outputs are better than no outputs. This problem is not fully appreciated until decisions of consequence must be based on hybridized systems. The phrase “I didn’t understand that” signals the onset of understanding the difference between marketing promises and actual system deliverables.

How many of those in my audience will agree with me? Darned few. My hunch is that most of those attending the conference will be looking to use “Big Data” as a way to generate revenue. I also think that only a handful of people will appreciate the computational challenges which hybridized systems can present.

Stephen E Arnold, May 8, 2013

Phi Beta Iota:  There are many severe analytic corruptions in the total concept of “big data.”  Most “big data” is like swiss cheese (reminiscent of NGA’s crummy Third World 1:50 combat chart data, still today), the data is driven by Industrial Era factors, and that data is simply not worth the money it takes to process especially when processing blind and processing mush.  The human factor continues to be repressed at just the time when it should be coming to the fore.  “Transformation” in the 21st Century is not going to come from technology as much as from an enhanced role for properly educated and totally connected humans able to operate in all languages and acquire “just right, just enough, just in time” data from OTHER HUMANS, while leveraging HUMAN-CENTRIC technologies.  As usual, the US complex has it upside down and inside out, and is ignoring, among many other vital elements, whole systems analytics, time-based analytics, and true cost economics.  A tiny example:  big data on “the economy” is stupid — it only covers the one fifth that is traditional “legal” and regulated money.  It does not cover System D dollars, barter and time dollars, and well as other forms of compensation.

See Also:

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2013 From Information Pathologies to Organizational Intelligence — Why Predictive Analytics on Industrial Era Data is Fraud, Waste, & Abuse

2013 Robert Steele Foreword to NATO Book on Public Intelligence for Public Health

2013 Robert Steele in HighGainBlog on Open and Secret Intelligence

2013 Robert Steele: Reflections on Inspectors General

2013 Robert Steele: Reflections on Lincoln, Principle, Compromise, Autonomous Internet & Citizen Intelligence / Counter-Intelligence 2.0 with Meta-RECAP

2012 Ishmael Jones (P) on The Human Factor

2012 PREPRINT: The Craft of Intelligence 3.4

2012 Reality Sandwich: The Open Source Everything Manifesto

2012 Robert Steele Answers PhD Student Questions

2012 Robert Steele: Addressing the Seven Sins of Foreign Policy — Why Defense, Not State, Is the Linch Pin for Global Engagement

2012 Robert Steele: Practical Reflections on UN Intelligence + UN RECAP

2012 Robert Steele: Reflections on Data as the New Oil BUT No One Is Serious About Holistic Analytics, True Cost Economics, Machine or Man-Machine Translation, or M4IS2

2012 Robert Steele: Reflections on the US Military — Redirection Essential — and a Prerequisite to Creating a 450-Ship Navy, a Long-Haul Air Force, and an Air-Liftable Army + Sanity RECAP

2012 Robert Steele: The Human Factor & The Human Environment: Concepts & Doctrine? Implications for Human & Open Source Intelligence 2.0

2012 Robert Steele: The Human Factor & The Human Environment: Contextual Trust for Sources & Methods

2012 Thomas Briggs on The Human Factor

2012 U.S. Naval Power in the 21st Century: 450-Ship Navy, <24 Hours to Anywhere, Peace from the Sea — Full Text Online

2011: Inteligencia Empresarial y Estrategia Competitiva en Mercados Internacional – Contexto y Desafio [Commercial Intelligence and Competitive Strategy in International Markets – Context and Challenge]

2011 Robert Steele: Global Trends 2030 – Gaps + RECAP

2011 Thinking About Revolution in the USA and Elsewhere (Full Text Online for Google Translate)

2010 M4IS2 Presentacion por Sur America (ANEPE Chile) — 2010 M4IS2 Briefing for South America

2010: OPINION–America’s Cyber Scam

2010 Julian Harston “Intelligence Assessment and Risk Analysis in Peacekeeping and Peace Support Operations – A Necessity”

2010 Reference: 5 Lessons From Outgoing Microsoft Software Architect Ray Ozzie

2008: Creating a Smart Nation (Full Text Online for Google Translate)

2008 Open Source Intelligence (Strategic) 2.0

2008 Rebalancing the Instruments of National Power (Full Text Online for Google Translate)

2008 The Substance of Governance

2006 Robert Steele: Reinventing Intelligence

2004 Simmons (US) to Schoomaker (US) Concern of Army Mis-Definition of Open Source Intelligence (OSINT) as a Category of Information Instead of a Transformational Discipline in its Own Right

2004 Simmons (US) & Schoomaker (US) Hearing on Army Transformation Remarks on Open Source Intelligence (OSINT)

2003 Information Peacekeeping & the Future of Intelligence – The United Nations, Smart Mobs, & the Seven Tribes (Full Text Online for Google Translate)

2003: Peacekeeping Intelligence Leadership Digest 1.0 (Full Text Online for Google Translate)

2002 Pinkham (US) Citizen Advocacy in the Information Age

2000 Sandman (US) Applied Human Intellect: Interpreting the Data Bits

1998 Hughes (US) Foreign Broadcast Information Service (FBIS) 1995-1998: Transition and Transformation

1995 Private Enterprise Intelligence – Its Potential Contribution to National Security (Full Text Online for Google Translate)

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Anthony Judge: Eliciting a Universe of Meaning

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Anthony Judge: The Cognitive Glass Ceiling — Enabling Questions, Challenged Audiences — Psychic Numbing and the Need for a Transformation of HOW We Think

Anthony Judge: Transforming and Interweaving the Ways of Being Stoned — Imagination, Promise, Rocks, Memorials, Petrification

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INTELLIGENCE with INTEGRITY: Preface 1.0

INTELLIGENCE with INTEGRITY Chapter 2: The InfoSphere & Its Enemies

INTELLIGENCE with INTEGRITY Chapter 3: The Human Factor

INTELLIGENCE with INTEGRITY: Chapter 5 Systems Thinking & True Cost Economics

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INTERVIEW: PBS Frontline with Robert Steele on Hackers

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John Taylor Gatto: The Ultimate History Lessons (1 Hour)

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Michel Bauwens: The New Rules of Innovation – Bottom-Up Solutions to Top-Down Problems

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Paul Fernhout: Open Letter to the Intelligence Advanced Programs Research Agency (IARPA)

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Richard Wright: It’s Only Money – Why the IC Continues to Fail & Robert Steele: 10% Grade – A Dishonorable Discharge Needed

Richard Wright: On DoD Transformation, Chuck Hagel, & Zionist Meddling

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SOCIAL SYSTEMS AND TRANSFORMATIONAL CHANGE

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Tom Atlee: Citizen Wisdom Councils – OUR Treasure

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Tom Atlee: Diversity Matters

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Tom Atlee: Seeking Leverage for Deep Transformation

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Way of the Truth

Winslow Wheeler: Marine Corps and the F-35 — Outright Lies, Deception, and a Total Lack of Intelligence with Integrity

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Worth A Look: A View from the Emergence Edge

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