Power of Declarative Analytics for Big Data

Sponsored Sessions Ballroom G
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Modern enterprises are performing complex analyses on increasingly large data sets to drive business decisions. Root cause analysis from system logs, social media analytics for customer retention, new customer acquisition and digital marketing are rapidly gaining importance. These tasks consist of three major analytic phases: text analytics / entity resolution, structured data processing, and predictive modeling. Traditionally these phases have been handled by a combination of custom code and separate systems such as ETL engines, relational databases, and statistical packages. However, the size of the datasets involved in these modern applications make it prohibitively expensive to move data across different specialized systems for analysis. This has resulted in the need for a single infrastructure that is sufficiently flexible to handle all these workloads. At IBM, we have embedded innovative analytics capabilities into our big data products to support each of these phases. By attending this insightful session, you will learn first-hand how advanced analytics are enabling modern enterprises to deal with big data challenges.

This session is sponsored by IBM

Shivakumar Vaithyanathan


Shivakumar Vaithyanathan is the IBM Chief Scientist for Text Analytics and the Department Manager of the Intelligent Information Systems Group at the IBM Almaden Research Center. Since joining IBM in 1998, he has been involved in multiple research areas including development of learning algorithms, especially for extremely high-dimensional sparse data. His department is currently involved in building systems for Scalable Unstructured Analytics, Enterprise Search and Large-scale machine learning and Statistical Modeling. Technologies developed in his department are embedded in multiple IBM big data products.


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