Courtesy of ITVAR News
Big Data Analytics is the new buzzword today in the IT
industry. It is slowly becoming a platform and an important
consideration that has come to dominate the wish list of any CIO
today. Big Data is normally seen as a successor to Business
Intelligence (BI), a tool almost similar to the former but yet
appearing slightly different when seen from a usage standpoint.
Vendors earlier offering Business Intelligence to its clients are
now seen to be scaling up to Big Data Analytics given its ability
to play with a huge amount of data, usually unstructured and
generating predictive insights of it. And they cite the reason
Big Data v/s Business Intelligence
The basic difference between Big Data tools and normal BI
tools can be better understood by showcasing people function in the
respective processes. "The advent of Big Data has resulted in a new
professional role created for analyzing the huge amounts of data on
a real-time basis, known as data scientists to extract meaningful
insights hidden in the avalanche of data found within and outside
their organizations. A Data Scientist is different from a
professional in the BI functions in a way that the former will go
beyond the capabilities of what many would call 'traditional
business intelligence (BI).' While traditional BI is interested in
the 'what and the where,' data scientists are interested in the
'how and why'," explains Amit Mehta, Director - Marketing, EMC
India & SAARC.
Data Scientists in that case are seen as the new heroes of
the Big Data era with their ability to do predictive analysis,
posit the right questions, analyze massive data sets and their
interest in inferring things that are not already present in the
data. "People with Traditional BI skillset can only tell you how
many widgets you sold in a region compared to last year. A data
scientist on the other hand can tell you why sales plummeted in the
Northwest compared to every other region - or at least would have a
hypothesis," Mehta clearly puts it.
If we look at the traditional definition of Big Data, it is a
set of unstructured data that requires algorithms and interactivity
in order to find the patterns it contains, with the ways to derive
the inferences determined only after the data has been collected.
"Essentially, Big Data can handle more data and is way faster than
BI, which means exploration and interactivity and in some cases
delivering results in less time than it takes to load a web page,"
opines Subroto Das, VP - Storage Business, IBM, India & South
Also, in the traditional Business Intelligence model, since
these tools are often used to simply create periodic reports, it is
possible to first clean the data, cross-check before processing and
analyzing it. "However, in the case of Big Data, structures vary
often as different data sources are tapped in ad hoc fashion or
because the sources are not from traditional RDBMS tables and so
cannot be simply pushed into a structured repository. In many
cases, the analysis needs to be run against the raw data before any
data cleansing processes have been run. This further complicates
the query process," points out Amit Malhotra, Director - Storage
Sales, JAPAC Systems Division, Oracle.
The views of Harmeet Malhotra, Director - IDM & Storage
Solutions Marketing - APJ, Dell are still however in favour of
Business Intelligence who somehow feels that Big Data, though a
known phenomenon to many has not picked up pace yet. "Traditional
BI tools are designed to handle a structured database and one can
run a query or analysis. But in case of unstructured data (i.e. Big
Data) the information is not stored in the database and it first
need to be extracted from different sources. So this is in fact a
big challenge for the person has to be really skilled and also
specific about what he is looking for."
In years to come…
So does this mean extinction of the traditional Business
Intelligence tools? Not exactly.
Though many believe Big Data to be fast replacing Business
Intelligence, there is a rising inclination towards clubbing the
richness of both these tools together, in relation to the existent
structured and unstructured data, co-relating and integrating them
in some way and then deriving some meaningful insights out of it.
The power of Business Intelligence has only been enlarged with the
inclusion of Big Data.
Big Data is also further believed to enhance the need for
both BI and analytics in times to come, not just because of the
volumes and velocity of the data involved but because of the
different nature of analysis required. This will result in tools
that extend from the core BI capabilities to handling such
different analysis types coming to the fore.