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Big Data Vendor Of The Week

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 BlueData®, provider of the leading Big-Data-as-a-Service (BDaaS) software platform, today announced BlueData EPIC™ version 3.0. This major new release provides increased scalability, enhanced networking, significant security and performance optimizations, and new functionality for distributed data science operations. With BlueData EPIC 3.0, enterprises can quickly and easily deploy large-scale production environments for Big Data analytics and data science running in Docker containers -- either on-premises, in the public cloud, or in a hybrid architecture.

Enterprise deployments of the BlueData EPIC software platform have 

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 Impetus Technologies, a big data software products and services company,  announced integration of a new, deep learning capability for its StreamAnalytix™ platform. Based on the TensorFlow™ open source software library for machine learning, this new capability is being demonstrated at the DataWorks Summit 2017 in San Jose, California, and showcases an image recognition application running on an Apache Spark Streaming pipeline on StreamAnalytix. The combination of streaming analytics and deep learning enables a new breed of applications and machine capabilities in industrial IoT, voice analytics and anomaly detection.

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Syncsort, a global leader in data liberation, integrity and integration solutions for next-generation analytics, announced new solutions that bring together its industry-leading Big Data Integration and Trillium data quality software to address enterprise requirements to support data governance and Customer 360 initiatives in the data lake.

 

An important development following Syncsort’s 

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 Cloudera, Inc the provider of the leading modern platform for machine learning and advanced analytics, announced the release of Cloudera Altus, a Platform-as-a-Service (PaaS) offering that makes it easier to run large-scale data processing applications on public cloud. The initial Altus service helps data engineers use on-demand infrastructure to speed the creation and operation of elastic data pipelines that power sophisticated, data-driven applications.

Data engineering applications like ETL (Extract, Transform and Load) or batch scoring are often large, batch-oriented workloads that run for a fixed period of time and help companies extract critical insights from raw data. Organizations can gain significant flexibility and efficiency advantages by running these pipelines on elastic infrastructure. Enterprises want to leverage cloud infrastructure alongside familiar large-scale data processing tools and technologies.

The...

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