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Topic: Big Data

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BlueData EPIC - making Big Data implementations easy

Summary:Big Data tools are complex and there are many "moving parts" to install, tune and deploy. The installation of the hardware and software can require weeks of work and require expertise that is simply unavailable in the mid-market. BlueData believes it has the solution.

By Dan Kusnetzky for Virtually Speaking | December 12, 2014 -- 14:30 GMT (06:30 PST)

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Several folks from BlueData, Kumar Sreekanti Co-founder and CEO, and Anant Chintamaneni Vice President, Product, stopped by to introduce me both to the company and its BlueData EPIC platform. The company believes that there are several things getting in the way of mid-market businesses adopting Big Data and analytics and it is doing its best to address them. The key phrase they kept touching on was "software defined infrastructure."

What's inhibiting Big Data adoption in the mid-market?

Big Data tools are complex and there are many "moving parts" to install, tune and deploy. The installation of the hardware and software can require weeks of work and require expertise that is simply unavailable in the mid-market (and in quite a few larger organizations as well.)

Another large part of success in using Big Data and analytics is learning to ask the right questions. This part, of course, is outside of BlueData's control and is firmly in the hands of the customer.

BlueData EPIC

The company has developed a cloud-based platform, BlueData EPIC, designed to simplify the installation and use of common Big Data tools. Setting up a cluster of systems to execute Big Data tools is only a small number of clicks away. Simple enough that even an industry analyst could use it.

The company has made it extremely simple to setup and use a cluster of virtual systems to conduct Big Data analysis and then scale it up or down as the company's requirements change.

EPIC appears to support many of the most popular Big Data tools. Here's how the company describes what it currently supports:

EPIC offers the top-hits library of Big Data applications available from the open source community to address a wide variety of use cases including MapReduce centric batch processing, interactive SQL and stream processing. For example, with BlueData EPIC, you can create standalone Apache Spark 1.0 clusters independent of a Hadoop distribution. With BlueData EPIC, you can also quickly create multiple clusters using different Hadoop distributions as well as different versions of the same distribution on common infrastructure.

Snapshot analysis

As I've pointed out in other reports, Big Data isn't just about gathering and processing large amounts of business and operational data. Its about asking the right questions. This means that successful Big Data applications center on people and creative thinking not just tools. This is also true for mid-market companies seeking to benefit from Big Data. It is clear, however, that BlueData is doing its best to address the complexity and difficulties involved with setting up and using Big Data clusters and tools.

What is clear, however, is that a company, regardless of its size, can't just buy its way into Big Data success. BlueData makes part of this process extremely simple. It can't overcome the tool-focus some customers constantly exhibit.

Some organizations are so wrapped up in the tools that they don't bring in the appropriate subject matter experts and experts on data analysis. A focus solely on the tools, such as Hadoop, using the R language, MongoDB, MariaDB, Splunk, and others, can lead to expensive failures that lead the company off track rather than helping shine a new light on important trends or new customer requirements.

Rather than really understanding what data is available, what data is needed and what role an expertise in computer science and applications, modeling, statistics, analytics and math play, some focus on the tools they need and simply believe that new levels of insight will come from their use.

What I've seen is that organizations can easily find themselves having done quite a bit of work to analyze machine and operational data and still not have a clear understanding of what is going on. Even worse, they can fool themselves into believing they understand what the data says and really have only proved out the old maxim "Garbage in/Garbage Out." Closely examining the wrong data or playing interesting, but wrong, statistical games with that data isn't likely to create more useful insight either.

Companies must understand that data science is built upon, but is different than business analytics. Business analysts would take the results provided by a business system, such as a customer relationship management system, and go on to make predictions about how a product will sell or what is important to customers. BlueData clearly understands this and believes that making the implementation of clusters and installation of software easy will help companies focus on what's really important, exploring available data to find interesting and useful nuggets of insight.

Is Big Data on your company's list of things to do in the coming year? If so, BlueData could be extremely helpful.

Topics: Big Data

About Dan Kusnetzky

Daniel Kusnetzky, a reformed software engineer and product manager, founded Kusnetzky Group LLC in 2006. He is responsible for research, publications, and operations. Mr. Kusnetzky has been involved with information technology since the late 1970s. Mr. Kusnetzky has been responsible for research operations at the 451 Group; corporate and... Full Bio

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Disclosure

The Kusnetzky Group LLC is an independent technology industry research firm that focuses on system software, virtualization and cloud computing infrastructure. Dan's opinions are based upon research, personal experiences and actual use of technology. They are not based upon the relationships the company may or may not have with suppliers, end user organizations, the media, consultants or other analysts. Dan's research is available on a subscription basis through Kusnetzky Group LLC. Dan's attendance at industry events or at client meetings may be sponsored by the client. Clients may provide hardware or software for testing prior to the publication of analysis that includes that product. Clients may also provide shirts, jackets, coffee cups, folders, backpacks, pens and other event tchotchke. While nice, these don't effect Dan's opinions or insight about those clients or their products.

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