Special Interest Group: Oil and Gas

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  • 1.  Education Suggestions re: Content Analytics?

    Posted 12-12-2016 15:45

    Hi Everyone,

    There is a whole lot of information out there about the "value" of Content Analytics, Autoclassification, etc... (ex: AIIM's recent "Using Analytics" whitepaper) but I'm having difficulty finding anything, anywhere, regarding the skills & education required to actually DO it.

    Anyone out there have some advice to give? I'd really like to extend my Records Management skills into the IT/CA realm and any advice on where to start would be a huge help! If there are Applied Content Analystics training programs out there, that'd be great! But even if I could know what skills I should obtain (ex: SQL Database Administration, programming languages to learn, or statistical skills to obtain) it'd be a good start!

    Thanks!

    Will

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    Will Wood
    Records & Information Management Analyst
    Calgary
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  • 2.  RE: Education Suggestions re: Content Analytics?

    Posted 12-13-2016 13:07
    Hi Will,

    Clearly understand what you are looking for but I am afraid there is
    only a small number of training areas to help understand true content
    analysis. I suggest you take a look at one of the most important
    training items you have at your fingers tips. AIIM has the Information
    Management and Business Process Management courses.

    I applied both of these methodologies to develop the Well Management
    Department's ( RasGas ) Body of Knowledge. The Data analysis section for
    Petroleum Engineering found it much similar to associate their data
    crawls using a similar method.

    Take the CIP coures http://www.aiim.org/Education-Section/CIP

    Take the BPM Master Class ??? February 14-17, 2017 - Amsterdam, NL
    http://www.aiim.org/SearchPage?keyword=bpm

    There is a London BPM Master Class and I believe one in Washington DC.

    I Developed a Management System with BPM methodology as the Umbrella and
    BPA as the heart of the system. This is where you need to start if your
    data is like the many companies out there with duplicate data and out of
    date information you need to clean it up and reorganize the information
    before you analyze anything.

    I did some additional self study to add in BPMM Business Process
    Maturity Model http://www.omg.org/spec/BPMM/ it is a long document but
    will worth a look and understanding.

    Take a look at the steps from the Management System it will help you out
    some.
    http://tqmservices.net/index.html

    Good luck




  • 3.  RE: Education Suggestions re: Content Analytics?

    Posted 12-16-2016 16:01
    Will,

    Last night at the Huntsville Association of Technology December meeting
    I met Mike Feltman of ISSAC Consulting. They specialize in data
    analytics you may wish to speak with Mike and see what he may suggest.

    Mike Feltman
    Systems Engineering and Innovations
    mike.feltman@...

    Best regards,
    Michael




  • 4.  RE: Education Suggestions re: Content Analytics?

    Posted 12-14-2016 04:33

    Hi WIll,

    Good question! If you are looking for courses, you may want to look into available online courses like https://www.mooc-list.com/categories/statistics-data-analysis This is a list of online courses across technologies and concepts. I have done a MOOC (Massive Open Online Course) earlier this year about a topic and it's a good way to learn from top experts in a virtual way.

    Best regards,

    Dennie

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    Dennie Heye
    Business Analyst Information Management
    Royal Dutch Shell



  • 5.  RE: Education Suggestions re: Content Analytics?

    Posted 12-17-2016 08:04

    Hello Will

    As regards unstructured information, the three key areas in my opinion are:

    1. Text Analytics (curation). There are free online courses from Stanford also Text Mining and Analytics - University of Illinois at Urbana-Champaign | Coursera and plenty on Python OpenSource.Welcome to Python.org I recommend teaching yourself using Python, plenty free on the web or buy a cheap O'Reilly book.

    2. Natural Language Processing (understanding). Python has an NLTK Library Natural Language Toolkit - NLTK 3.0 documentation and there are lot of books on this.

    3. Machine Learning (Prediction). This can include using neural networks (e.g. word2vec), Topic Modelling etc. to surface latent patterns in text. For auto-classification or auto-categorization (big difference) check out Pointwise Mutual Information Measure as an algorithm, great for generating discriminatory clues.

    Use of Knowledge Organization Systems (KOS) like thesauri, taxonomies, authority lists and rules are key to mix with the statistical: Hybrid is best!

    Put all these three components together and you can also build apps that some marketer's are calling 'insight engines' or 'cognitive search' as they augment human thinking and mimic in very simple and limited way how 'we think', but because they can use more information than we can read they can suggest what we may miss or what we see (but don't see because we are biased).

    You may find these posts I made of interest on slideshare,  Paul Cleverley's Presentations on SlideShare some of them cover text analytics and its all free.

    If you would like a chat to get started, more than happy to share what I know to the community from an academic perspective.

    Merry Christmas!

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    Paul Cleverley
    Robert Gordon University
    www.paulhcleverley.com