|By Gerry Grealish||
|April 15, 2014 10:00 AM EDT||
While Big Data and the cloud are often thought of as going hand in hand, some enterprises still hesitate to place large amounts of proprietary data online. Enterprises decide to keep their large data sets stored locally for a variety of reasons including the possibility of security breaches, data processing errors, access issues and difficulty of meeting corporate or industry compliance / privacy requirements. Enterprises with a global presence are also finding they need to operate in an increasingly stricter data sharing environment. In fact, data residency policies from countries like the UK, Germany, Australlia and China can make housing data certain types of sensitive data within clouds in countries like the U.S. extremely challenging.
Despite these concerns, business imperatives are pressuring many enterprise CIOs and CEOs to move large amounts of data to the cloud. In fact, a recent report cited a 58% growth of the Big Data market in 2013 and predicts a high rate of growth over the next few years. This growth can be attributed to the ability of cloud-based Big Data applications to help enterprises move beyond the hindrances of heavily siloed data storage methods to an improved level of data sharing, access and analysis. Improved collaboration and insights from Big Data initiatives helps healthcare, government, technology and other organizations gain key competitive advantages and achieve rapid breakthroughs on a variety of sector-based issues. Just last week, Information Week highlighted Merck's use of Big Data sets to speed up vaccination development.
The Future of Big Data Online
For those enterprises that rely on processing and analyzing data in their daily business operations - whether it be for product development or service innovation - it is becoming essential from a competitive standpoint to have access to the efficiencies and benefits of Big Data applications online. Ideally, public cloud providers would be able to provide the security and compliance capabilities to fully meet industry regulations and geographical compliance requirements, but they frequently cannot for a certain portion of the most sensitive data, such as PHI and medical test results in Healthcare.
For enterprises wanting to capitalize on Big Data applications in the cloud while meeting still maintaining their security policies and industry compliance mandates, we recommend (1) classifying the sensitivity level of all "cloud-bound" data and (2) using a solution such as Perspecsys' AppProtex Cloud Data Control Gateway to encrypt/tokenize those fields that should not be stored or processed in cloud environments in the clear. This approach enables IT departments to give the business units access to the Big Data services they demand while still satisfying the data privacy directives of compliance regimes such as HIPAA, CJIS, GLBA, and PCI DSS.
PerspecSys Inc. is a leading provider of cloud data tokenization and cloud encryption solutions that enable mission-critical cloud applications to be adopted throughout the enterprise. Cloud security companies like PerspecSys remove the technical, legal and financial risks of placing sensitive company data in the cloud. PerspecSys accomplishes this for many large, heavily regulated companies across the world by never allowing sensitive data to leave a customer's network, while maintaining the functionality of cloud applications. For more information please visit perspecsys.com or follow on Twitter @perspecsys.
The 17th International Cloud Expo has announced that its Call for Papers is open. 17th International Cloud Expo, to be held November 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA, brings together Cloud Computing, APM, APIs, Microservices, Security, Big Data, Internet of Things, DevOps and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding business opportunity. Submit your speaking proposal today!
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