Predictive analytics describes any approach to data mining with four attributes: an emphasis on prediction (rather than description, classification or clustering), rapid analysis measured in hours or days (rather than the stereotypical months of traditional data mining), an emphasis on the business relevance of the resulting insights (no ivory tower analyses) and (increasingly) an emphasis on ease of use, thus making the tools accessible to business users.

1. Predictive Analytics, Contextual Computing, and
Big Data
By: Ahmed Banafa, Distinguished Tenured Staff | Faculty | SME | E-Learning Expert | Four-time
winner of instructor of the year award
Predictive analytics describes any approach to data mining with four attributes: an emphasis on
prediction (rather than description, classification or clustering), rapid analysis measured in hours
or days (rather than the stereotypical months of traditional data mining), an emphasis on the
business relevance of the resulting insights (no ivory tower analyses) and (increasingly) an
emphasis on ease of use, thus making the tools accessible to business users. (Gartner)
Source: SAS

2. Predictive Analytics & Contextual Computing
Cloud and mobility change the delivery and use of technology, and usher in the age of Apps and
services, as in Apps through Mobile devices, and Infrastructure as a Service, Software
applications as a Service.Mobile and Cloud are being joined by two other mega-trends that are
now underway: one of these is predictive analytics and the other is contextual computing.
Predictive analytics
Predictive analytics combs through historical data to make predictions about something
occurring in the future. It is already being put to use for business to consumer marketing, and
plenty of the big business intelligence suppliers are already servicing customer needs for pent-up
business demands.
An example of this is predicting – with more certainty – the likelihood of a specific person and
segments of the population who will purchase an automobile in the next three months based on
an analysis of past purchase behavior, Internet searches, financial conditions and a lot of other
information. Beyond being able to predict when someone is likely to purchase something like an
automobile, predictive computing also takes it a step forward by being able to predict what kind
of brand and offer the person is likely to respond to – or not.
Where does the data for predictive analytics come from? It comes from what you did (you’re
behavior) to what people’s interests are (internet searches and books read), how marketers look
at you and a group of similarly inclined people (your segmentation) and behaviors you exhibited
in the past (which cars you rented and purchased for example).
Contextual Computing
The age of contextual computing is just starting, with a lot of experimental jabs occurring in fits
and starts, including a variety of data reuses by Google, Yahoo, Facebook, Foursquare, Yelp,
Microsoft, IBM, the insurance industry, financial service firms, the travel industry, the healthcare
industry and the retail industry among others. An example of this is Google Now, a compendium
of applications that promise to “help you out” as it were.
As a personal aid and concierge, Google Now is but one of many new experiments in being more
predictive within the context of the user. These experiments promise to take predictive analytics
to another level by adding your social connections, what you know and believe, how you
respond to stimuli and learn (think Google Glass) to what your interests are and what your
behavior is (what you actually did) to make the power of analytic prediction even more precise.
The commercial interests in these technologies and experiments are strong. After all, marketers
will be able to more precisely target their next customer or retain current customers with much
less cost than current methods.

3. Predictive Analytics and Big Data
Predictive analytics is an enabler of Big Data: Businesses collect vast amounts of real-time
customer data and predictive analytics uses this historical data, combined with customer insight,
to predict future events. Predictive analytics enable organizations to use big data (both stored and
real-time) to move from a historical view to a forward-looking perspective of the customer.
The research firm Ovum expects a significant wave of business technology ramp-ups in 2014, in
response to the market demand. They predict a growing third-party vendor and IT services
ecosystem that creates Big Data tools and solutions for the enterprise data warehousing and
applications markets.
This growing trend is occurring as SQL and Hadoop platforms are diversifying, adopting
multiple personalities, and providing overlapping functions. According to Ovum’s latest market
study, SQL queries can now be run against Hadoop, and many SQL databases will be able to
handle JSON (JavaScript Object Notation: is a lightweight data-interchange format. It is easy
for humans to read and write. It is easy for machines to parse and generate) document-centric
queries.
The Trends to Watch for Predictive Analytics and Big Data in 2014 include:
Analytic data platforms are adding multiple personalities.
A Big Data enterprise application market is emerging.
There is NoSQL life beyond Hadoop.
Data tiering is predominant in real-time data platforms.
However, the drawback is that some of these engines or approaches are quite early in
development; in many cases, implementations are still proprietary.
References
http://www.predictiveanalyticsworld.com/predictive_analytics.php
http://www.webopedia.com/TERM/P/predictive_analytics.html
http://www.gartner.com/it-glossary/predictive-analytics
http://www.cloudcomputing-news.net/blog-hub/2013/nov/29/what-are-big-data-and-predictive-analytics-
market-trends-for-2014/
http://cloudtimes.org/2013/11/30/predictive-analytics-is-the-next-growing-sector-in-big-data-market/
http://www.itpolicycompliance.com/blog/predictive-analytics-contextual-computing/
: http://data-informed.com/gartner-researchers-predictive-analytics-to-gain-traction-in-
business/#sthash.VUDCVDRw.dpuf
http://blogs.sas.com/content/subconsciousmusings/2013/01/11/why-people-and-process-matter-in-
addition-to-great-technology-in-predictive-analytics/
http://www.npr.org/blogs/alltechconsidered/2014/03/17/290125070/computers-that-know-what-you-
need-before-you-ask