SAN FRANCISCO – June 19, 2013 – Concurrent, Inc., the enterprise Big Data application platform company, today announced that Paco Nathan, director of Data Science, will deliver a talk, titled “Pattern – an open source project for migrating predictive models from SAS, R, Microstrategy®, etc., onto Hadoop” at the 6th Annual Hadoop Summit North America, taking place June 26-27, 2013 in San Jose, Calif. This two-day event will feature Apache Hadoop™ thought leaders who will showcase successful Hadoop use cases, share development tips and tricks and educate organizations about how to best leverage Apache Hadoop as a key constituent in their enterprise data architecture.

Details At-A-Glance

What: “Pattern – an open source project for migrating predictive models from SAS, R, Microstrategy®, etc., onto Hadoop” speaking session at Hadoop Summit
Who: Paco Nathan, director of Data Science of Concurrent, Inc., the company behind the Cascading™ application framework
When: Wednesday, June 26 at 4:55 p.m. PDT
Where: San Jose Convention Center
How: Register at http://www.hadoopsummit.org/san-jose/register/

Session Description

Pattern is a free, open source project, which takes models trained in popular analytics tools, such as SAS®, Microstrategy®, R and SQL Server, and runs them at scale on Apache Hadoop. This machine-learning library, based on the popular Cascading framework, works by translating PMML into data workflows and can be quickly deployed on your Apache Hadoop data. PMML models can be run in a pre-defined JAR file with no coding required and can also be combined with other flows based on ANSI SQL (Lingual), Scala (Scalding) and Clojure (Cascalog) to meet enterprise requirements. Benefits include greatly reduced development costs and less licensing issues at scale, while leveraging a combination of Apache Hadoop clusters, existing intellectual property in predictive models, and the core competencies of analytics staff. Sample code in this talk will show apps using predictive models built in SAS and R. In addition, examples will show how to compare variations of models for large-scale customer experiments. Portions of this material come from the O’Reilly book “Enterprise Data Workflows with Cascading,” publishing on July 10, 2013.

About the Speaker

Paco Nathan is director of Data Science at Concurrent, Inc., where he leads the company’s developer outreach program. He has a dual background from Stanford in math/statistics and distributed computing, and has more than 25 years experience in thetechnology industry. Nathan is an expert in Hadoop, R, predictive analytics, machine learning and natural language processing.

Supporting Resources

Cascading website: http://www.cascading.org
Pattern website: http://www.cascading.org/pattern
Concurrent website: http://www.concurrentinc.com
Contact Us: http://www.concurrentinc.com/contact
Follow us on Twitter: http://www.twitter.com/concurrent

About Concurrent, Inc.

Concurrent, Inc.’s vision is to become the #1 software platform choice for Big Data applications. Concurrent builds application infrastructure products that are designed to help enterprises create, deploy, run and manage data processing applications at scale on Apache Hadoop. Concurrent is the mind behind Cascading™, the most widely used and deployed technology for Big Data applications with more than 75,000+ user downloads a month. Used by thousands of data driven businesses including Twitter, eBay, The Climate Corp, and Etsy, Cascading is the de-facto standard in open source application infrastructure technology. Concurrent is headquartered in San Francisco. Visit Concurrent online at http://www.concurrentinc.com.

Media Contact
Danielle Salvato-Earl
Kulesa Faul for Concurrent, Inc.
(650) 340-1982
concurrent@kulesafaul.com

Concurrent, Inc. Teams with Hortonworks to Bring Rapid Application Development and Deployment To Hadoop

Cascading and the Hortonworks Data Platform Make Hadoop Application Development and Machine-Learning Deployment Quick and Easy

SAN FRANCISCO – June 18, 2013 – Concurrent, Inc., the enterprise Big Data application platform company, today announced that Hortonworks has certified its Cascadingapplication framework against the Hortonworks Data Platform (HDP). The certification ensures that enterprises can take advantage of Concurrent’s Cascading application framework and HDP to ease Hadoop Big Data application development and bring machine-learning applications to the masses.

Together, with the simplicity and flexibility of Cascading and the reliability and stability of the HDP, companies can rapidly build, test and deploy new data transformation and refinement, data processing, analytics and machine-learning applications. Enterprises can now leverage existing skill sets, core competencies and product investments by carrying them over to HDP via the standards-based technology – Java, ANSI SQL and machine-learning standards. Analysts and data scientists familiar with these can now easily run predictive data models at scale and integrate ETL, data preparation and predictive analytics in the same application, greatly reducing time to production and unlocking access to large Hadoop data sets.

HDP is the only 100-percent open source ApacheTM Hadoop®-based data management platform. HDP allows users to capture, process and share data in any format and at scale. Built and packaged by the core architects, builders and operators of Hadoop, HDP includes all of the necessary components to manage a cluster at scale and uncover business insights from existing and new big data sources. Cascading is the most widely used and deployed application framework for building robust, enterprise Big Data applications on Hadoop. Recognized companies, including
The Climate Corporation, eBay, Etsy, FlightCaster, iCrossing, Razorfish, Trulia, TeleNav and Twitter, are using Cascading to streamline data processing, data filtering and workflow optimization for large volumes of unstructured and semi-structured data. Cascading is also at the core of popular language extensions including PyCascading (Python + Cascading), Scalding (Scala + Cascading) and Cascalog (Clojure + Cascading) – open source projects sponsored by Twitter. Cascading has become the most reliable and repeatable way of building and deploying Big Data applications.

Supporting Quotes

“Hadoop adoption continues to grow as organizations look to take advantage of new data types and build new applications for the enterprise. By combining our enterprisegrade data platform and unparalleled growing ecosystem with the power, maturity and broad platform support of Concurrent’s Cascading application framework, we have now closed the modeling, development and production loop for all data-oriented applications.” -Shaun Connolly, Vice President, Corporate Strategy of Hortonworks

“Cascading is committed to driving simplicity into application development on Hadoop. By partnering with Hortonworks, we are combining the power of two premier Big Data technologies to deliver a holistic solution that further enables enterprises to drive differentiation through data.”
-Gary Nakamura, CEO of Concurrent, Inc.

Supporting Resources

Cascading website: http://www.cascading.org
Hortonworks website: http://www.hortonworks.com
Learn more with the Hortonworks Sandbox
Concurrent website: http://www.concurrentinc.com
Contact Us: http://www.concurrentinc.com/contact
Follow us on Twitter: http://www.twitter.com/concurrent

About Concurrent, Inc.

Concurrent, Inc.’s vision is to become the #1 software platform choice for Big Data applications. Concurrent builds application infrastructure products that are designed to help enterprises create, deploy, run and manage data processing applications at scale on Apache Hadoop.
Concurrent is the mind behind Cascading™, the most widely used and deployed technology for Big Data applications with more than 75,000+ user downloads a month. Used by thousands of data driven businesses including Twitter, eBay, The Climate Corp and Etsy, Cascading is the de-facto standard in open source application infrastructure technology. Concurrent is headquartered in San Francisco. Visit Concurrent online athttp://www.concurrentinc.com.

Media Contact
Danielle Salvato-Earl
Kulesa Faul for Concurrent, Inc.
(650) 340 1982
concurrent@kulesafaul.com

Launches Pattern, in combination with Cascading and Lingual; completes the ensemble and bridges the gap for enterprises to fulfill the promise of Hadoop in the enterprise

SAN FRANCISCO – May 21, 2013 – Concurrent, Inc., the enterprise Big Data application platform company, today introduced Pattern, a free, open source, standard-based scoring engine that enables analysts and data scientists to quickly deploy machine-learning applications on Apache Hadoop™. Leveraging the power and broad platform support of the Cascading application framework, Pattern lowers the barrier to Hadoop adoption by enabling companies to leverage existing intellectual property (IP) in predictive models, existing investments in software tooling and the core competencies of existing analytics staff to run Big Data applications from existing machine-learning models using Predictive Model Markup Language (PMML) or through a simple programming interface.

Hadoop is rapidly becoming the tool of choice for tackling enterprise Big Data analytics needs in an effort to make the most of growing volumes of unstructured and semi-structured data. The need for Hadoop to easily integrate with existing data management and analytics systems, however, has created a real barrier to comprehensive Hadoop adoption.

Enter Pattern: PMML for Cascading and Hadoop

With the introduction of Pattern, companies can now leverage existing skill sets, core competencies and product investments by carrying them over to Hadoop via the standards-based PMML technology. PMML is the standard export format for tools, such as R, MicroStrategies® and SAS®; and with Pattern, analysts and data scientists familiar with these technologies can now run predictive data models at scale and integrate ETL, data preparation and predictive analytics in the same application to greatly reduce development time and unlock accessibility to large Hadoop data sets. Pattern in turn will enable a whole new class of use cases and simplify experiments.

Pattern runs on Cascading, the most widely used and deployed application framework for building robust, enterprise Big Data applications on Hadoop. Recognized companies, including The Climate Corporation, eBay, Etsy, FlightCaster, iCrossing, Razorfish, Trulia, TeleNav and Twitter, are using Cascading to streamline data processing, data filtering and workflow optimization for large volumes of unstructured and semi-structured data. Cascading is also at the core of popular language extensions including PyCascading (Python + Cascading), Scalding (Scala + Cascading) and Cascalog (Clojure + Cascading) – open source projects sponsored by Twitter. Cascading has become the most reliable and repeatable way of building and deploying Big Data applications.

By leveraging the Cascading framework, enterprises can apply Java, SQL and predictive modeling investments, and combine the respective outputs of multiple departments into a single application on Hadoop. This is a powerful step forward in delivering on the full promise of the business of Big Data.

Supporting Quotes

“Pattern facilitates AgilOne to deploy a variety of advanced machine-learning algorithms for our cloud-based predictive marketing intelligence solution. As a self-service SaaS offering, Pattern allows us to evaluate multiple models and push the clients’ best models into our high performance scoring system. The PMML interface allows our advanced clients to deploy custom models.”
-Antony Arokiasamy, Senior Software Architect, AgilOne

“Concurrent is tearing down barriers for mass Hadoop adoption. With Pattern, we have cleared another path by enabling data scientists to more easily bring their work to production. When combined, Cascading, Lingual and Pattern close the modeling, development and production loop for all data oriented applications. The combination of the three is the application ensemble for further enabling enterprises to drive differentiation through data.”
-Chris Wensel, CTO and Founder, Concurrent, Inc.

Supporting Resources

Pattern website: http://www.cascading.org/pattern
Cascading website: http://www.cascading.org
Lingual website: http://www.cascading.org/lingual
Company: http://www.concurrentinc.com
Contact Us: http://www.concurrentinc.com/contact
Follow us on Twitter: http://twitter.com/concurrent

Availability and Pricing

Pattern is a free, open source software and available under the Apache 2.0 License. To learn more about the Pattern project, visit http://www.cascading.org/pattern. Concurrent also offers standard and premium support subscriptions for enterprise use. To learn more about Concurrent’s offerings, please visit http://www.concurrentinc.com.

About Concurrent, Inc.

Concurrent, Inc.’s vision is to become the #1 software platform choice for Big Data applications. Concurrent builds application infrastructure products that are designed to help enterprises create, deploy, run and manage data processing applications at scale on Apache Hadoop.

Concurrent is the mind behind Cascading™, the most widely used and deployed technology for Big Data applications with more than 75,000+ user downloads a month. Used by thousands of data driven businesses including Twitter, eBay, The Climate Corp and Etsy, Cascading is the de-facto standard in open source application infrastructure technology. Concurrent is headquartered in San Francisco. Visit Concurrent online athttp://www.concurrentinc.com.

Media Contact
Danielle Salvato-Earl
Kulesa Faul for Concurrent, Inc.
(650) 340 1982
concurrent@kulesafaul.com

MapR provides direct integration with Concurrent’s open source Cascading framework in Hadoop distribution

SAN FRANCISCO – May 15, 2013 – Concurrent, Inc., the enterprise Big Data application platform company, today announced a partnership with MapR Technologies, Inc.™, the Hadoop technology leader, to expand usage of Apache Hadoop™ in the enterprise. Under this partnership, the MapR Distribution for Apache Hadoop has been certified compatible with Concurrent’s Cascading application framework and is now supported for production use by Concurrent’s customers. The MapR platform will also include an open-source application Multitool, based on Cascading, which allows users to search, find and process data files from the command line across a Hadoop cluster.

Apache Hadoop open source has been adopted quickly in “new economy” companies, but the requirement to write and manage complex MapReduce jobs and the inability to integrate the analytics with enterprise applications have slowed the broader mass adoption. By combining the MapR dependability, data protection and performance innovations with the power and broad platform support of Concurrent’s Cascading application framework, the two companies are bringing a simple-to-use, enterprise-grade development framework and deployment platform together for large-scale data analysis.

The MapR enterprise-grade platform supports a broad set of mission-critical and real-time production uses and brings unprecedented dependability, ease-of-use and world-record speed to Hadoop, NoSQL, database and streaming applications in one unified Big Data platform. MapR is the only distribution that enables Linux applications and commands to access data directly in the cluster via the NFS interface that is available with all MapR editions. Leading Fortune 100 and Web 2.0 companies, across industries, use MapR to analyze hundreds of billions of objects a day. MapR’s broad partner ecosystem includes market leaders such as Amazon, Cisco and Google.

Cascading is the most widely used and deployed application framework for building robust, enterprise Big Data applications on Hadoop. Recognized companies, including The Climate Corporation, eBay, Etsy, FlightCaster, iCrossing, Razorfish, Trulia, TeleNav and Twitter are using Cascading to streamline data processing, data filtering and workflow optimization for large volumes of unstructured and semi-structured data. Cascading is also at the core of popular language extensions including PyCascading (Python + Cascading), Scalding (Scala + Cascading) and Cascalog (Clojure + Cascading) – open source projects sponsored by Twitter. Cascading has become the most reliable and repeatable way of building and deploying Big Data applications.

Supporting Quotes

“MapR is committed to continual innovation and growth in the Hadoop community. We’ve now fully certified the MapR Distribution with Cascading 2.1, a tool that has helped drive industry momentum and is widely leveraged by organizations whose business depends on data analysis. By partnering with Concurrent, we further expand on the promise of Hadoop by building a more robust and comprehensive solution for our customers.”
-John Schroeder, CEO and Co-Founder, MapR Technologies

“Enterprises in the business of data have the most to gain from using Hadoop, and MapR is the only Hadoop distribution that provides full data protection, no single points of failure, improved performance, and dramatic ease of use advantages to the enterprise. With today’s partnership, we have combined the power of Cascading with the reliability, scalability and performance of the MapR enterprise-grade platform, delivering one the most comprehensive offerings for Hadoop applications.”
-Gary Nakamura, CEO of Concurrent, Inc.

Supporting Resources

Cascading website: http://cascading.org
MapR website: http://www.mapr.com
Company: http://www.concurrentinc.com
Contact Us: http://concurrentinc.com/contact
Follow us on Twitter: http://twitter.com/concurrent

About MapR Technologies

MapR delivers on the promise of Hadoop with a proven, enterprise-grade platform that supports a broad set of mission-critical and real-time production uses. MapR brings unprecedented dependability, ease-of-use and world-record speed to Hadoop, NoSQL, database and streaming applications in one unified Big Data platform. MapR is used across financial services, retail, media, healthcare, manufacturing, telecommunications and government organizations as well as by leading Fortune 100 and Web 2.0 companies. Amazon, Cisco and Google are part of MapR’s broad partner ecosystem. Investors include Lightspeed Venture Partners, Mayfield Fund, NEA, and Redpoint Ventures. Connect with MapR on Facebook, LinkedIn and Twitter.

About Concurrent, Inc.

Concurrent, Inc. is the enterprise Big Data application platform company. Concurrent simplifies Big Data application development, deployment and management on Apache Hadoop. We are the company behind Cascading, the most widely used and deployed technology for building Big Data applications with more than 75,000 user downloads a month. Enterprises including Twitter, eBay, The Climate Corporation and Etsy all rely on Concurrent’s technology to drive their Big Data deployments. Concurrent is headquartered in San Francisco. Investors include Rembrandt Venture Partners and True Ventures. Connect with Concurrent on LinkedIn and Twitter.

Visit Concurrent Inc online at http://concurrentinc.com

Media Contact
Danielle Salvato-Earl
Kulesa Faul for Concurrent, Inc.
(650) 340 1982
concurrent@kulesafaul.com