- Learn Everything You Need to Know about the Most Widely Used and Deployed Technology
for Big Data Applications; Online Access Now Available
- Author Paco Nathan to Speak at OSCON 2013
SAN FRANCISCO – July 10, 2013 – Concurrent, Inc., the enterprise Big Data application platform company, today announced the book release of “Enterprise Data Workflowswith Cascading” by Paco Nathan, director of data science at Concurrent. Published by O’Reilly Media, the hands-on book introduces readers to Cascading™, the most widely used and deployed technology for Big Data applications with more than 75,000+ user downloads a month. The Cascading framework enables users to quickly and easily build powerful data processing applications on Apache Hadoop that span ETL, data preparation and analytics with one unified development framework. The book offers developers, data scientists and system/IT administrators a quick overview on Cascading’s streamlined approach to data processing, data filtering and workflow optimization using sample applications based on Java, ANSI SQL, PMML, Scala and Clojure. Thousands of companies such as Etsy, Razorfish, TeleNav and Twitter already use Cascading for business-critical applications.
With “Enterprise Data Workflows with Cascading,” readers will learn how to:
• Examine best practices for using data science in enterprise-scale applications
• Use workflows beyond MapReduce to integrate to other frameworks and existing IT systems/tools
• Quickly build and test applications, and instantly deploy them onto Apache Hadoop
• Easily discover, model and analyze both unstructured and semi-structured data
• Seamlessly move and scale application deployments from development to production, regardless of cluster location or data size
To purchase a copy of “Enterprise Data Workflows with Cascading” now, visit: http://oreil.ly/19Gc9y6
About the Author
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 mathematics and statistics, and distributed computing. With more than 25 years experience in the technology industry, Nathan is an expert in Hadoop, R, predictive analytics, machine learning and natural language processing. This book release comes on the heels of Concurrent’s recent announcement of Pattern, a free, open source, standard-based scoring engine, built on Cascading, that enables analysts and data scientists to quickly deploy machine-learning applications on Apache Hadoop. Cascading provides the most comprehensive application framework for Hadoop. With the addition of Lingual (ANSI SQL) and Pattern (PMML), Cascading bridges the gap and allows enterprises to use existing skills and systems to easily develop and deploy robust applications on Hadoop. The combination of the three (Java, SQL, PMML) completes the application ensemble.
Learn More About Cascading at OSCON
Nathan will speak on Cascading at O’Reilly OSCON in Portland on July 25, 2013. For more information on his session, “Using Cascalog to Build an App with City of Palo Alto Open Data,” and to register, please visit:http://bit.ly/1azv6oS.
● Enterprise Data Workflows with Cascading:http://oreil.ly/19Gc9y6
● Cascading website: http://www.cascading.org
● Company: 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.
Kulesa Faul for Concurrent, Inc.
(650) 340 1982