How would you define Big Data?
Every day, organizations create huge amount of data -- both
structured and unstructured. On top of that, the
organizations are not just struggling to keep up with the rate and
pace of this huge data, but are also unable to use it in a
meaningful way to improve products, services and customer
experience. This huge data that we are talking about is Big
Data.
Organizations have adopted technologies that can handle data
such as data warehousing (DW). But the increase in the amount of
data has resulted in complexities. This has led to a trend wherein
the organizations are moving from basic reporting to analytics and
now heading towards predictive analytics. And to enable predictive
analysis, IT departments are integrating Big Data with already
stored data.
Explain how predictive analysis can help
organizations?
It is not only organizations; citizens like us too would like to
predict the future. For instance, I love Mumbai city but quite
often I get frustrated with the city’s unpredictable traffic.
Imagine how convenient it would have been if we could predict the
traffic well in advance and save our commuting time.
The organizations today need to be proactive and not reactive
and should be aware of the future of their business. Earlier, the
analytics were transaction based but in today’s competitive
world, customer experience plays a very critical role. Hence,
it’s extremely crucial for the organizations to provide more
value to their customers and understand their views and opinion.
And predictive analysis can help them in doing so.
In order to be in business, grow and have a competitive edge,
organizations need predictive analytics. For example, if a
company’s sales are down for a particular region, analytics
will only help to find out the reasons for the same but predictive
analytics will find out what is most likely to happen in the
future.
According to you, which industry verticals will be more
benefitted by predictive analytics?
Predictive analysis is beneficial to most of the industry
verticals such as telecom, banking, retail, healthcare, government
etc. For instance, IBM’s InfoSphere Streams solution at a
neonatal ICU helps to detect the life threatening conditions of a
child at least two hours before the child actually gets the
disease. Similarly, to manage a city better, the government can use
predictive analytics. For example, the city of Stockholm is using
InfoSphere Streams that helps the residents of the city to get
real-time information on traffic flow, travel times and the best
commuting options. Even, predictive analytics can help
telecommunications companies to identify the reasons for customer
churn. The companies can then address the issues and increase
subscriber base and revenues.
Thus, whether an organization is a law enforcement agency
analyzing video images as they are streaming into their
organization, a bank analyzing a decade of transactional data to
identify patterns that indicate fraud or a retailer combining
customer purchase information with social media sentiment analysis,
Big Data can help organizations use their data as a strategic
asset.
Discuss IBM’s strategies for Big
Data?
IBM offers the broadest platform for Big Data, addressing all three
dimensions of the Big Data challenge - variety, velocity and
volume. InfoSphere BigInsights and InfoSphere Streams are the core
technologies of IBM's platform for Big Data. IBM’s
acquisition of Cognos, SPSS and OpenPages has further strengthened
IBM’s business analytics portfolio.
About Author
Vinita Gupta is Principal Correspondent at InformationWeek India. Vinita has over six years experience in IT reporting and has interviewed more than 500 business executives. She has a PG Diploma in Business Management from NMIMS and Post Graduate Degree in Communication and Journalism from Mumbai University
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