Weekly Big Data review: Hadoop gets smarter and more secure
To move beyond the Big Data hype, business users need a new breed of applications that can not only accommodate information growth, but also separate the signal from the noise to improve decision making. These are the kind of apps Resolution Analytics wants customers to build using the latest release of its enterprise R distribution, which saves developers the trouble of optimizing their code for multiple platforms.
By making it more portable, Resolution is aligning the statistical language with the heterogeneous nature of big data environments. The new “write once, deploy anywhere” feature of Revolution R Enterprise 7 (RRE 7) is complemented by an automation component that simplifies application integration and lets data scientists take advantage of front end analytical tools like Tableau with minimum hassle.
Making data more consumable is a top priority for the ecosystem, but with the rapid pace of change in today’s cyber threat landscape, it’s becoming increasingly difficult for vendors to find the balance between accessibility and security. This is the issue IBM is trying to tackle with “fully homomorphic encryption,” a newly patented technology that makes it possible to analyze encrypted data without decrypting it. The patent uses a mathematical object known as an “ideal lattice” that let users extract insights without accessing any confidential information, a major stumbling block for hackers that has the added benefit of greatly simplifying regulatory compliance.
RainStor is also jumping into the security fray with a database offering for Hadoop that provides native authorization and authentication capabilities on top of HDFS. This is achieved with on-disk encryption, data masking, support for Kerberos and a host of other features designed to safeguard enterprise clusters while making it easier for end users to interact with their information.
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