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MapR Releases New Ecosystem Pack with Optimized Security and Performance for Apache Spark

MapR Technologies, Inc., the provider of the Converged Data Platform that converges the essential data management and application processing technologies on a single, horizontally scalable platform, announced its next major release of the MapR Ecosystem Pack (MEP) program. MEP is a broad set of open source ecosystem projects that enable big data applications running on the MapR Converged Data Platform with inter-project compatibility.

Databricks Launches New Edition of Its Spark-Based Cloud Platform for Data Engineers

Databricks, the company founded by the creators of the popular Apache Spark project and providers of the leading Spark-based cloud platform for data science, announced an edition of its cloud platform optimized specifically for data engineering workloads called Databricks for Data Engineering.

5 Common Myths Around Virtualizing Big Data (Number 3 is SANdalous!)

In this contributed article, Justin Murray, Technical Marketing Manager at VMware, discusses 5 common myths around virtualizing big data. Big data burst on to the scene a little over a decade ago. Today it is not an obscure term confined to just a handful of bleeding edge companies. It is a mainstream trend that every enterprise undergoing a digital transformation journey has adopted. The technology landscape around big data has broadened dramatically.

Information Builders Offers iWay Big Data Integrator on Microsoft Azure Marketplace Cloud

Information Builders, a leader in business intelligence (BI) and analytics, data integrity, and integration solutions, announced that it is offering its iWay Big Data Integrator (iBDI) product via the cloud on the Microsoft Azure Marketplace.

Data as a Critical Element in the Discovery and Delivery of Smart Energy

In this contributed article, Jules S. Damji, an Apache Spark Community Evangelist with Databricks, shows how as the value of data continues to grow, the next-generation smart grid should become a reality, benefiting utility companies and consumers alike.

Pepperdata Integrates Performance into DevOps for Big Data

Pepperdata, the Big Data performance company, announced it is expanding its product portfolio with Pepperdata Application Profiler, providing Hadoop and Spark developers with easy to understand recommendations for improving job performance. Application Profiler is currently available in early access and will be generally available in the second quarter of 2017.

EnterpriseDB Announces New Apache Spark Connecter to Speed Postgres Big Data Processing

EnterpriseDB® (EDB™), the database platform company for digital business, announced the general availability of a new version of the EDB Postgres Data Adapter for Hadoop with compatibility for the Apache Spark cluster computing framework. The new version gives organizations the ability to combine analytic workloads based on the Hadoop Distributed File System (HDFS) with operational data in Postgres, using an Apache Spark interface.

The Leaky Pipeline Problem -
 Making your Mark as a Woman in Big Data

insideBIGDATA was on hand for the recent Spark Summit East 2017 conference in Boston, and one of the more compelling presentations was by Kavitha Mariappan, VP Marketing at Databricks. The talk focused on the premise that despite the tremendous growth and opportunities in big data today, women still play a small role in this arena.

Percipient Launches SparkPLUS to Solve Apache Spark’s Out-of-memory Problems

Percipient, a Singapore-based startup, is launching a revolutionary solution to address the memory issues incurred by users of open source platform, Apache Spark. By delivering unified data a priori to the Spark platform, Percipient’s SparkPLUS solution is able to multiply the platform’s computing space, thereby greatly enhancing its utility for real time and analytical applications.

Monte Carlo Simulations in Ad-Lift Measurement Using Spark

In this talk from Spark Summit East 2016, Prasad Chalasani explores some of the challenges that arise in setting up scalable simulations in a specific application, and share some solutions and lessons learned along the way, in the realms of mathematics and programming.