In the world of information technology, big data represents the
large and complex collection of data growing at a relentless rate. According to
Intel, prior to the year 2003, mankind generated approximately 5 exabytes of
data. It is estimated that by the close of 2012, global data will have grown to
2.7 zettabytes, which is about 500 times the amount of data stated above; by
2015, that number is expected to triple in size. Financial services providers, retailer
databases, logistics, healthcare, and various other industries are capturing
more data than ever before. The advent of public social media as a primary
method of communication and information sharing holds stake in the
responsibility for these record numbers of data as well.
Organizations are now focusing their efforts on how to most
effectively harness the colossal amounts of data available to them. Whether
searching for ways to improve business operations, gain insight into competitor
activity, understand consumer behavior, or apply big data to scientific
research, it is widely accepted that big data analytics is the current platform
for computing innovation. Below I have added a short, fun video created by
Intel that explains what big data is and why it is important.
A primary concern in big data analytics is how to visualize
and present these enormous amounts of data in an effective manner. Data
visualization is a concept that has been around for ages. It can be
simplistically defined as the graphical representation of information. Data
visualization communicates the key aspects of complex data sets in more
coherent and meaningful ways. Graphs, pie charts, and maps are tools familiar
to everyone that fit in the category of data visualization. Visualization is
extremely important because it allows humans to understand and better assess a
given dataset, rather than looking at the raw, varying information and attempting
to derive a conclusion.
However, big data visualization presents a different and
much more complex animal. With so many differing data types and approaches to
storage and processing, the question plaguing the minds of business leaders and
researchers is how to extract and display this valuable information in a way
that is easily understandable and applicable to their current processes. An
overwhelming amount of data being compiled is freeform in nature, meaning that
it cannot be confined to structured predefined tables. Richard Schaeffer, former
information assurance director for NSA and head of the consulting firm
Riverbank Associates, was quoted saying, “Big data involves datasets that
grow so large they become awkward to work with using traditional database
management tools. Organizations that handle large volumes of data such as the
intelligence community and scientific researchers know how to capture, collect
and store large datasets. They are also learning how to more effectively index
data. The problem areas are processing, analytics and visualization. In fact,
visualization of big data, rendering it into graphical means for analysis,
might be the most significant problem organizations will face in the future.”
This visualization issue sited by Mr. Schaeffer paired with
its high demand has been the driving force behind a new wave of innovation.
Organizations are transitioning from very traditional graphics to interactive
and dynamic graphical representations, often with the built in capability to
update in real-time and automatically make changes within the visualized data. From
heat maps to infographics and so on, technology moguls are pioneering the path
to a new era in data visualization.
In July of 2012, The Forrester Wave™ released an in-depth report
titled “Advanced Data Visualization Platforms, Q3 2012”. In the report,
co-authored by Boris Evelson and Noel Yuhanna, they stated “Now, through ADV,
potential exists for nontraditional and more visually rich approaches, especially
in regard to more complex (i.e., thousands of dimensions or attributes) or
larger (i.e., billions of rows) data sets, to reveal insights not possible
through conventional means.” They then go on to site and explain the six
capabilities that they believe differentiate a static graph from advanced data
visualization graphics: dynamic data content, visual querying,
multiple-dimension linked visualization, animated visualization,
personalization, and business-actionable alerts. The report also details the
leading innovators in the ADV arena, with Tableau Software, IBM, Information
Builders, SAS, SAP Tibco Software, and Oracle leading the industry charge. Here
is a link to the report referenced above:
Be sure to keep your eyes peeled for the continued growth
and development of data analytics, and in particular data visualization. This
is the new frontier for innovation and will transform the way by which the data
available is harnessed and utilized.
CLUVIS
CLUVIS
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