International Big Data Conference 2016

Big Data analytics has without doubt become mainstream in 2016. Companies are initiating data science projects on Big Data platforms, offloading ETL processing to Hadoop, and archiving to Hadoop. Also more capability being put in the hands of business analysts and data scientists using self-service tools for data preparation, analytics or both. Apache Spark has become even more of a force in the analytics market with many different information management and analytical tools now integrated with Spark and using Spark Streaming, Spark SQL, MLlib, and GraphX both on-premises and in the Cloud. New Spark analytics libraries have also emerged. Also the data deluge continues to grow.

More and more data is coming into the enterprise and without a doubt, information management and governance in a Big Data environment is turning into a huge issue. Therefore the emphasis has shifted to cataloging and classification of data as a way to improve data governance and applying policies according to how the data has been classified. In addition, centralized Data Lakes are giving way to distributed Big Data environments with multiple relational and NoSQL data stores now being used in a hybrid Cloud and on-premises computing environment. Big Data Governance including Big Data Security is therefore now paramount. In addition, the latency of data is being pushed closer to real-time as companies sell smart products and leverage the data generated by the Internet of Things.

This Conference aims to provide ‘how to’ sessions on Big Data and analytics to show how to exploit the latest technology and how to create a data driven enterprise. It provides sessions on advanced analytics and how to extend information management and data governance to encompass Big Data Security, self-service data integration, and governance of a Data Lake. It also for the first time includes real case studies of how Big Data is being implemented in practice by many companies in the Italian and wider European marketplace.

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