“Big Data” - The 2012 Word of the Year
Melissa Stevens 270005B76W MELISSAS@US.IBM.COM | | Tags:  data-security ibm-security ibmsecurity big-data security
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This post is contributed by Kim Madia, World Wide Product Marketing Manager for Infosphere.
Working at IBM, I have been fortunate enough to be a part of launching big data platforms to clients. Big data is more than simply a matter of size; it is an opportunity to find insights in new and emerging types of data and content, to make businesses more agile, and to answer questions that were previously considered beyond reach.
Living in the technology space, terms like sentiment analysis, analytics, and high velocity data are becoming familiar. However, it is interesting for me to see how those outside of the technology business are engaging in the big data phenomenon. Geoff Nunberg, teacher at the University of California at Berkeley, recently made a case for big data as the 2012 word of the year. Another example, The New York Times has ran articles about how the US held its first “big data presidential election” in 2012.
One topic that is picking up steam in popular media, and I expect will get even greater focus in 2013, is privacy. In this era of big data, understanding privacy couldn’t be more important. Privacy isn’t static and can’t be easily defined. Privacy also has different meanings across businesses, industries and cultures. Privacy rules therefore are a constant source of debate. For example, a person’s zip code might want to be kept private during a trip to a health care clinic but may want to be disclosed to a retail establishment.
Sometimes privacy is confused with security or anonymity. Though related, these terms are not the same. Privacy is defined as the ability to control use of information in different contexts.
Technology is available to help deliver privacy. Intelligent data masking inside big data platforms makes analytics possible while also keeping private information out of sight. A focus on privacy will fundamentally change how big data platforms are adopted. The end goal is to provide aggregated sensitive data to an analytics platform while protecting privacy. I believe in 2013 we will see more debate between IT professionals and governance regulators about how to create more effective privacy policies.
To learn more about data masking, you might be interested in this analyst research: Understanding and Selecting Data Masking Solutions.
IBM delivers intelligent data masking through the InfoSphere Optim Data Masking portfolio.