October - 2013 - issue > CEO Spotlight

Transform Into a Data-driven Organization

Ravi Condamoor
Founder & CEO-Serendio
Tuesday, October 1, 2013
Ravi Condamoor
Headquartered in Santa Clara, Serendio helps companies transform multi-structured data into insight and decisions through the use of big data, text analytics, machine learning, and predictive science.

Data-driven decision making has always been the Holy Grail for enterprises that want to quickly adapt to the changing needs of the customer or business conditions. As your data builds within multiple data stores in abundant formats, you may find your organization has accumulated billions of rows of data with hundreds of millions of data combinations. The key impediments towards morphing into a complete data-driven business include content silos created by the various applications, the diverse formats that such content come in and lack of a unified analytics platform that does descriptive, predictive, and prescriptive analytics of all the content regardless of format or type. So the solution to the big data challenge then becomes obvious – big data requires high-performance analytics to process and figure out what's important and what's not.

With the volume, velocity, and variety of data exploding, newer NoSql and Hadoop technology have been leading the way in breaking down the content silos and providing a common analytics platform across the enterprise. But the NoSql and Hadoop technologies are still in the initial stage of maturity and adoption cycle to completely count out SQL technology. In future, a hybrid model or a purpose-built architecture involving Sql, NoSql and Hadoop technologies will be the way for all successful data-driven enterprises.

Analytics will be pervasive in all walks of business – sales, marketing, product development, and customer support. The digital cookie crumbs that we all leave behind when we browse the web, send a text, upload vacation pictures on Facebook, or download a coupon on to our mobile phone, will be fully exploited by businesses and government agencies for hyper-targeting of content, products, and services. But it will also raise concerns for potential loss of privacy, security, and anonymity amongst ordinary, unsuspecting citizens. The industry will see Responsible Analytics as a key area of innovation in future; enforced by a combination of regulation, peer policing, technology, and best practices.
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