How to Transform into an Insight-Driven 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.
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. Companies like Automic are looking to address this problem through automation, and in such a way that the automation stack itself doesn’t become overly complex as well. The company’s Automic Workload Automation system is certified for the Hortonworks Data Platform 2.3 and has received YARN Ready and Security Ready badges as well. It enables full integration of Big Data workflows into Hortonworks, plus centralized orchestration of MapReduce, Hive and other tasks that extend across distributed environments.
Many SMEs might not see the advantages that Big Data can bring to their business yet, says Cloudera’s Daniel Ng, but it is important to remember that even today’s behemoths were start-ups once and a key element in their success was the successful use of data. From the very beginning, no less than Amazon showed the world the value of tracking not just what people bought but what they viewed, how they navigated the site and how various promotions fared. Eventually, its algorithms became so powerful that they could predict what people would buy next. With emerging Big Data platforms becoming so low-cost, easy to deploy and simple to use, it won’t be long before small companies will need to embrace the change in order to remain competitive.
It was inevitable that the infrastructure needed to support Big Data would get smaller and cheaper while the tools and processes would become simpler, but this doesn’t mean enterprises large and small are now on the easy street to digital transformation. The real work starts when you attempt to apply these platforms to real-world situations, and success will depend very much on not just what you query in your databases, but how you query it.
Technology can give you Big Data, but it’s up to you to turn it into smart data.
Arthur Cole writes about infrastructure for IT Business Edge. Cole has been covering the high-tech media and computing industries for more than 20 years, having served as editor of TV Technology, Video Technology News, Internet News and Multimedia Weekly. His contributions have appeared in Communications Today and Enterprise Networking Planet and as web content for numerous high-tech clients like TwinStrata and Carpathia. Follow Art on Twitter @acole602.
