Teradata (NYSE: TDC), the leading analytic data solutions company, today announced that it has identified five key big data analytic trends that will shape the business landscape in 2013 and beyond.
"The future of business belongs to those enterprises that embrace the big data
analytics movement and use it to their advantage," said Scott Gnau, president,
Teradata Labs. "Teradata is committed to helping customers simplify the
mysteries of data and analytic technologies. Business leaders and chief
information officers (CIOs) who are the quickest to adopt big analytic solutions
in a unified architecture will be the most competitive. Successful companies are
already extending the value of classic analytics by integrating cutting-edge big
data technologies and outsmarting their competitors."
Teradata has pinpointed the five big data analytic trends for 2013:
1. The Rise of the Big Data Discovery Platform
The Discovery Platform will become an indispensable part of big data strategy.
The Discovery Platform provides knowledge workers--including business analysts
and data scientists alike--with a reliable workbench from which to explore and
perform experiments on big data, at scale, at a fraction of the time and cost
required with traditional approaches. This capability has traditionally required
up-front data sampling and modeling, as well as specialized skills. Discovery
platforms allow companies to innovate on analytics by testing hypothesis and
"failing fast" to uncover new insights in data. In addition, the discovery
platform "lets the data speak;" this dialogue between the data and knowledge
workers enables the business to identify new trends and insights that can lead
to benefits like better consumer personalization or fraud detection.
A discovery platform must support a variety of interfaces in a single platform,
including Structured Query Language (SQL), business intelligence tools (BI),
statistics, and next-generation MapReduce analytics. In contrast to traditional
systems, a discovery platform needs to impose very few requirements on how the
data is modeled so that businesses can easily and quickly combine new and
existing sources of data to speed up the discovery process.
2. Explosive Big Data Application Growth
The number of big data applications will explode over the next three years; the
growth will start in 2013. Development of these applications will present
challenges to CIOs because the skills required to develop big data applications
are different - and more sophisticated - than the skills required to develop
traditional applications. In the future, big data will be consumed by knowledge
workers and applications alike. This new generation of applications, including
web and mobile, will be powered by big data insights in multiple industries.
This will drive a huge competitive advantage enabling business to clearly see
new opportunities to engage with their consumers.
3. From Fragmentation to a Unified Architecture
The variety of new big data technologies and platforms from which to choose will
be both a blessing and a curse. In 2013, some organizations will deploy the new
big data platforms in an IT environment that lacks a unified architecture and
does not integrate data, metadata, security, and administration. The use of big
data analytic point solutions in a fragmented IT environment can kill the
promise that big data can provide better insights by doing more analytics on all
data. Such deployments will quickly lead to a torrent of failed big data
projects.
It doesn't have to be that way. Tighter integration of technologies that support
enterprise standards and leverage existing investments in analytical tools is
essential for the success of big data initiatives. Deploying applications in a
unified enterprise environment makes analytics simpler, faster, and more
powerful; while reducing deployment and operational costs. The new analytic
capability provided by the applications can catapult an organization forward.
4. Blending of Capabilities
To be competitive, organizations need the capability of both big data analytics
(MapReduce and procedural analytics at scale) and traditional analytics (SQL)
that run within a relational database management system. As a result, big data
analytics will not come close to replacing traditional analytics in 2013. The
debate about which one will replace the other is unproductive. CIOs and business
users will begin to blend the capabilities of the two to meet the intelligence
needs of the business. Tools and technologies that provide a native blending of
classic and new data analytics techniques will have an inherent advantage as the
market realizes their value in 2013.
5. Storage is Not Enough
CIOs will move beyond focusing on hardware for storage of massive amounts of
diverse big data to developing an analytic process that is repeatable and
provides business value. Then, CIOs will be able to transition away from buying
point solutions to deploying big data platforms. Advanced technology is now
field-tested and available that can store and transform massive volumes of
diverse data into usable intelligence for deployment across the organization.
CIOs will look to their existing information management vendors to provide
innovation without disruption. The CIO and their organizations that are the
quickest to adopt the now-available big analytic solutions will be the most
competitive.
