BIG DATA AND LEARNING ANALYTICS
A definition of big data in terms of size and/or complexity:
"Big Data” is a term used to describe data
sets so large and/or complex that they become awkward to work with using
traditional database management tools. An example is the use of Learning Analytics techniques to find trends in comments on a course in a Learning Management System (LMS) in conjunction with
comments in Social Media.
A useful reference:
Franks, B 2012, Taming the
Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with Advanced
Analytics, Wiley
This book has
some good sections on analytics practices and teams, and isn't just about Big
Data. It also has sections on Enterprise Analytical Datasets (ADS), creating secure data, Model
and Score Management, statistical tools, and Analytic Sandbox types.
Learning Analytics is an area set
to grow rapidly:
Acknowledgement: New Media Consortium
A definition of
Learning Analytics:
Learning analytics is the measurement,
control, collection, and analysis of data about learners, educators, and their environments.
Initiatives based on an understanding of these elements and how they interact
can lead to superior outcomes.
The following text provides a thorough coverage of most Analytics,
Predictive Modeling, and Data Science techniques:
Ratner, B 2011, Statistical and Machine-Learning Data Mining: Techniques for Better
Predictive Modeling and Analysis of Big Data", CRC Press
Interesting chapters include Principal Components Analysis (PCA),
Smoothing, Segmentation with Chi-squared Automatic Interaction Detection
(CHAID), look-alike profiles, data treatments, and the principles of genetic
modeling.
Science Fiction becomes reality:
Most enterprises don’t have the amazing power of Watson yet,
but capability can be built across time.
Acknowledgement: Network World
Quote:
“Any sufficiently advanced technology is indistinguishable from
magic.”, Arthur C. Clarke
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