By Jim Zimmermann
A recent McKinsey Global Institute study titled “Big data: The next frontier for innovation, competition, and productivity” defines Big Data as “datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze.” Big Analytics is the process of analyzing Big Data to derive value for the business. Both of these topics are latest hot topics for analysts covering technology – and many of them point out a severe lack of talent to address Big Data and Big Analytics.
So what’s the big deal about Big Data and Big Analytics? All successful organizations collect lots of data – about customers, purchases, manufacturing, supply chain, employees, their web sites, etc. Much of the data that has been collected is just sitting somewhere waiting for someone to decide if it may have value to the organization or to decide that the data is of little or no value. Big Data and Big Analytics have been successfully employed in both the private and public sector to use the data to derive business value. Organizations that have invested in analyzing their Big Data repositories have often discovered information or trends that have a profound impact on the future direction of their organization.
The push towards Big Data and Big Analytics fuels an organization’s need for advanced technology-based analytics tools as well as top analytical talent to perform analysis of the data. Further, analysts point to a need to build an internal analytical culture, and they claim that despite early successes, analytics are not integral to decision-making processes in most organizations.
To address these talent gaps, organizations are looking for ways to acquire or build the talent needed to get business value out of their data. Unfortunately, there is not a lot of talent available to hire, so many companies are being forced to look at ways to develop the talent in-house. Skillsoft offers a number of excellent Big Data and analytics resources in several Books24x7 collections – ITPro, BusinessPro and AnalystPerspectives. Below are a number of recent titles in the ITPro collection that can be used to help develop internal Big Data and analytics skills (note that the links require a subscription to the appropriate Books24x7 ITPro collection):
- Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition – by Bruce Ratner, Auerbach Publications © 2012 (544 pages)
- Social Network Mining, Analysis and Research Trends: Techniques and Applications – by I-Hsien Ting, Tzung-Pei Hong and Leon S.L. Wang (eds), IGI Global © 2012 (429 pages)
- Decision Management Systems: A Practical Guide to Using Business Rules and Predictive Analytics – by James Taylor , IBM Press © 2012 (316 pages)
- Data Mining: Practical Machine Learning Tools and Techniques, Third Edition – by Ian H. Witten, Eibe Frank and Mark A. Hall, Morgan Kaufmann Publishers © 2011 (665 pages)
- Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management, Third Edition – by Gordon S. Linoff and Michael J.A. Berry, John Wiley & Sons © 2011 (888 pages)
For AnalystPerspectives subscribers, a new AnalystPerspectives Consensus Report on Big Data and Big Analytics in the Public Sector is also available.