For most enterprises, Big Data has moved from being just a buzzword or a science project to the recognition that Big Data can generate tactical and strategic competitive advantage as well as being a value creator for the business. There are plenty of choices in terms of the underlying hardware technology; a variety of Hadoop distributions or NoSQL databases; and numerous technologies that help enterprise enable internal datasets to be integrated with external datasets.

1. Communiqué Sponsored by Greenplum, a division of EMC
Lowering the Barriers to Entry for Big Data February, 2013
Current Overview
For most enterprises, Big Data has moved from being just a buzzword or a science project
to the recognition that Big Data can generate tactical and strategic competitive advantage
as well as being a value creator for the business.
So many businesses have heeded the advice from Neuralytix with respects to Big Data:
If you’re not doing it, your competitors are!™
However, recognition does not always translate to realization. A major impediment for most
enterprises is not the infrastructure. There are plenty of choices in terms of the underlying
hardware technology; a variety of Hadoop distributions or NoSQL databases; and numerous
technologies that help enterprise enable internal datasets to be integrated with external
datasets. For most enterprises, the lack of Big Data skills is singularly the biggest impediment in
embarking on the Big Data journey.
There are several ways of addressing this challenge:
 Hire data scientists and Big Data experts;
 Outsource the Big Data processing to service providers; or
 Create custom code for each project.
Each of these options have its own relative pros and cons. But all of these options typically
isolate data that are used with current processes, applications, and other intelligence that have
been purpose built for the enterprise.
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2. This makes Big Data not only a challenge from a skills perspective, but fiscally challenging.
Ideally, what enterprises are looking for, is an opportunity to integrate existing and
perhaps even proprietary intelligence with the new datasets that Hadoop and other Big
Data technologies provide.
For many enterprises, they have made considerable investments in developing and
retaining relational database administrators (DBAs). Many of these DBAs have coded
custom queries to support the enterprise.
So it naturally begs the question, what would be better than to protect and extend the
talent that already exists in the enterprise. But unlike the unstructured data with which
most Big Data experts and data scientists typically manage; DBAs and business intelligence
(BI) specialists are more accustomed to dealing with traditional structured query language
(SQL).
One way to achieve this, is to provide extensions into the Hadoop framework that allow
existing ANSI-standard SQL to act on data within Hadoop; and to allow the framework to
extend its reach beyond unstructured data into structured and relational databases.
Neuraspective™
The Hadoop framework consists of a menagerie of projects: HDFS, Hbase, Hive, Pig,
Zookeeper, Map/Reduce, and R just to name a few. However, these projects do not enable
enterprises to leverage the assets and resources already in place without requiring data
migration from existing datasets to the Hadoop framework.
To address these challenges, EMC’s new Hadoop distribution, Pivotal HD, brings together
its Greenplum MPP database, its new “Dynamic Pipelining” technology, and the ability to
perform true SQL processing for Hadoop.
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3. Pivotal HD addresses the key barriers to entry for Big Data. It provides libraries that allow
existing business intelligence, and practically any ANSI standard SQL queries to operate
within the Hadoop framework.
Additionally, Pivotal HD also provides the libraries that connect tables from relational
databases, such as Oracle, as an external table, and enable Hadoop operations to be
performed against the data from these tables.
So what?
With the introduction of Pivotal HD, this means that enterprises have the opportunity to
evolve their existing database environments into Big Data environments organically.
Existing SQL compliant processes are not lost. Instead, these processes can now address
any data that can be managed within the Hadoop framework.
Many enterprises think of investment protection purely in terms of hardware. However,
the intellectual property investment can be as great (or in many cases, greater). Unlike
hardware, which suffers from depreciation and deterioration, intellectual property such as
queries, processes and concepts developed from within an enterprise appreciates in value.
By bringing the capabilities of a true SQL parallel database to Hadoop, it provides
enterprises with the ability to create new potential from its existing data, information and
protects the investment made in infrastructure.
About Neuralytix™
Neuralytix™ is a bespoke strategy consultancy that is focused on Driving Business Value
with Technology™. Our philosophy aims to bridge the gap between the boardroom and the
computer room™ by helping stakeholders better understand the business value of
technology. Visit http://www.neuralytix.com to learn more.
Copyright
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email at sales@neuralytix.com.
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