Student: Data Analysis and Big Data Essay

Submitted By shiweisun
Words: 2356
Pages: 10

T+D, August 2012 v66 i8 p54(5)
8 Realities learning professionals need to know about analytics. Ellen Wagner.
Full Text: COPYRIGHT 2012 American Society for Training & Development, Inc.
As our lives have moved online, we are all increasingly aware of the emerging, exploding interest in what has come to be known as Big Data. Big Data refers to the massive data warehouses filled with servers that store the so-called "digital breadcrumbs" of our online shopping transactions, movie selections, Facebook likes, tweets, website viewing activities, and more. Descriptive, inferential, and predictive analyses are applied to those massive data sets to look for patterns that provide insight into our desires, preferences, and behaviors. For example, retailers analyze detailed transactions to better understand customers' shopping patterns and to forecast demand, optimize merchandising, and increase the lift of their promotions. Internet companies study website information to enhance site visitors' experiences and provide advertisers with more granular targeted advertising.
Big Data analyses have ramped up everyone's expectations of what may be possible for improving accountability, transparency, and quality in all facets of our lives, from the marketplace to the workplace, to civic engagement, and at every point in the education and training value chain, including learning and development. They also have raised serious questions about the degree to which we understand which variables are truly predictive of desired action states, for whom and under what conditions they predict, and the confidence with which the predictions are made.
Put data to work

Learning and development organizations collect vast amounts of digital information in their learning management systems and enterprise resource planning systems. However, few organizations are systematic about using enterprise data at any level, Kirkpatrick or otherwise, to proactively anticipate emerging problem areas and recognize new opportunities for strategic alignment, performance support, and enterprise growth.
Today's explosive interest in analytics is fueled by the recognition that enterprise success in the era of the "new normal" depends on forward-thinking strategic alignment between goals and operations, agility, and the recognition of the proverbial right place to be and right time to be there.
According to the 2010 Gartner Research Report, Hype Cycle for Pattern-Based Strategy, business leaders want to move from reacting to events that will have major effects on strategy and operations to proactively seeking patterns that might indicate an impending event. Learning and development organizations simply cannot live outside today's enterprise focus on the measurable, tangible results now driving IT, operations, finance, and other mission-critical applications. More to the point, learning and development organizations have emerging opportunities for putting their data to work in new and highly productive ways that will lead to demonstrable impact and alignment with business goals and enterprise strategic directions.
Technological developments certainly have served as catalysts for the move toward Big Data. Virtual data ware-houses and the cloud make it possible to collect, manage, and maintain massive numbers of records. In addition, sophisticated technology platforms provide the computing power necessary for grinding through calculations and turning the mass of numbers into meaningful patterns.
It is clear that Big Data and other more localized data analysis a la Google Analytics have the potential to inform learning professionals to anticipate the support that will be required to enable under a variety of changing market conditions. These data will be able to inform enterprises about where investments provide the greatest return. The promise of providing personalized, optimized experiences for learning and performance support that may eventually correlate with