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CEO at Kahuna, a cross-channel marketing automation platform that uses artificial intelligence to engage and convert consumers on the right device at the right time. Kahuna is trusted by modern digital products such as Dollar Shave Club, Yelp, GoPro and others. Prior to Kahuna, Sameer was SVP for Enterprise Social and Collaborative Software in SAP/ SuccessFactors cloud business unit. Sameer has been cited in publications such as CNBC Business, The New York Times, and Forbes on high performing organizations, leadership, and trends in enterprise software.

One response to “BigData, Mobile and Cloud Convergence: The Elephants”

  1. H.Maraj

    Being able to analyze big data to extract value from it is key. We are learning how important the role of a data scientist is in predictive analytics and business intelligence, for solving big data related problems. HPCC Systems has recently released its open source distributed Machine Learning (ML) library and the underlying linear algebra Matrix arithmetic libraries, to assist data scientists and developers in these type of tasks. These algorithms leverage the distributed nature of the HPCC Systems architecture, providing for extreme scalability in large feature sets, particularly with hundreds or thousands of features and millions of entries. The real advantage is that, now, data scientists will be able to do machine learning with full parallelization, on Big Data. By leveraging the power of ECL on the HPCC Systems platform, the need for employing many Java developers on a Big Data problem is avoided, and this reduces the overall cost and delivery time of the projects. Learn more at