by Angela Guess
In a recent interview David Loshin discussed emerging methods for handling Big Data security issues. Loshin said, “I had an interesting conversation a few weeks back about whether data in the cloud is better protected than data that’s sitting in your own systems. We drilled down into that in the context of big data, such as that managed by Hadoop and those types of frameworks; we discussed the fact that the people who are developing Hadoop applications or MapReduce applications are developers. They are presuming access to the data, and the data sitting out on a collection of nodes and in some massively parallel configurations — presumably, that’s data in an uncontrolled environment… and there is even greater opportunity for exposure.”
Loshin continued, “Essentially, the data needs to be moved over to the framework, be it Hadoop or whatever. It’s then exposed as the analysis is being done, and then the results are integrated back in, or reconnected back to, for example, some traditional data warehouse or business intelligence framework. When you’re looking at large collections of data, there’s the potential once again for lots of data being exposed. On the other hand, if you’re creating a controlled environment where there is no other means of getting access, one might say that there might be an opportunity for increasing the protection, if you’re instituting your development framework in the right way.”
