Rethink BI : Business Insights over Business Intelligence
The purpose of this business insights thought leadership blog is to share the HP point of view on industry trends such as Big Data and Real Time Analytics, and provide updates on key innovations and solutions.

Big Data architecture in the New Style of IT—Part 2

In this second part of our series, we ask Greg Battas, CTO of Business Intelligence Solutions for HP Converged Systems to help us understand the next steps in grappling with Big Data. Last time, we discussed how enterprises are building a series of solutions based on Hadoop clusters that sit alongside Converged Infrastructure solutions. This week, we learn how that might lead to even more Big Data headaches, and explore a possible solution to the problem.


iStock_000023930618Small.pngTo pick up where we left off, remember that Greg is seeing more and more customers building successive Big Data solutions based on a one-cluster-one-solution platform. Typically these sit alongside already converved infrasture solutions. This leads to an application-centric data center. As Greg says, “Not good.” We pick up the conversation from that point.


So … where do we go from here?

GB: Good question. I think we need to step back a bit and look at how these systems evolved. We began handling Big Data with the idea that we were going to move away from proprietary storage and proprietary data bases. In the early days the idea was to use industry-standard servers with direct attach storage. A distributed file system sat on top of that storage, and then we would build parallel progamming on top of that, to accept the data and so on.


The second area focussed on moving compute as close to the data as possible, with direct attach storage and incredibly resilient software. The pitch was: You get enormous benefit by moving compute close to the data. And all of this has to happen in a very strong open source culture with evolving, innovate ecosystems, such as Hadoop.


Well this presents a couple of challenges.


First off, whenever you want to provision new servers in this environment, you have to move the data. And that takes time. It’s not easy to reconfigure the data as the business demands. Another pitfall is that there isn’t an easy way to share data between clusters. In fact, it has to be copied between clusters to leverage the hardware and software resources. So Big Data in this case, is getting bigger. Not good. So naturally, one of the questions we ask at HP is what can we do about that? And how can we start to converge these systems?


In our next post, we’ll explore possible solutions to this problem. But for now, check out this short video post from HP Discover 2013 in Las Vegas. Here, HP Product Manager, Lisa Boyd, discusses the enterprise-ready, turn-key HP AppSystem for Apache Hadoop platform. This solution is factory assembled and configured so that it is ready to use on the day of the delivery.


Greg_Battas_badge_176x304_tcm245_1428057_tcm245_1422290_32_tcm245-1428057.pngAbout Greg Battas

Greg’s background in solving business problems for customers — in particular those in the retail, telecommunications and financial services sectors — and in product development for relational database management systems, has played a critical role in helping bridge the gap between the viewpoints of IT and business decision-makers to explain how to use technology to solve challenging organizational issues.

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