Big Data for the Small Enterprise

Big Data is not just for the big enterprise. Organizations of all sizes can leverage the power of large data sets and advanced analytics to derive the kinds of insight needed to fuel next-gen business opportunities.

But creating the big infrastructure needed to support Big Data is no easy task, nor is finding the right way to use it in order to produce the highest level of return. Until now, that is.

In recent weeks, a number of platforms have emerged that aim to remove much of the complexity from big data, allowing mid-sized and even small enterprises to get started without a lot of lead time or a major hit to the capital budget.

New Jersey’s Wipro, which provides IT and business process consulting to a variety of enterprise clients, recently opened up its Big Data Ready Enterprise (BDRE) platform to make it easier and faster to implement under a broader unified data framework. The system is available on GitHub under the Apache 2.0 license, offering full lifecycle management across ingest, process, analyze and other functions associated with the big data-facing “data lake.” Besides being easier to implement, Wipro says, an open platform is also easier to customize for key industry verticals and use cases.

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Meanwhile, a company called Cazena is out with a Big Data as a Service (BDaaS) platform on the Microsoft Azure cloud that offers on-demand scalability plus easy integration into legacy environments using existing security and other tools. The system supports multiple database engines, such as Cloudera and, more recently, Greenplum, and users can integrate both data lake and data mart presences under a single cloud architecture to provide a varied analytic pipeline for diverse data sets. The company says it can provide plug-and-pay deployment without disrupting existing workflows or developing massive data projects from scratch, and it can also be utilized for data sources outside the enterprise network, such as feedback from social media and the IoT.

Since there are many moving parts to big data infrastructure, many organizations aren’t just put off by the size of the program, but the complexity.

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