Infoworks.io, the leader in Enterprise Data Operations and Orchestration (EDO2) systems, announces that the company is co-sponsoring a Unified Data Analytics virtual workshop with Databricks and Microsoft Azure this week. “Unifying Data Pipelines, Business Analytics and Machine Learning with Apache Spark™” will cover best practices for enterprises to use powerful technologies to simplify and scale data and machine learning efforts. Included in the workshop will be a presentation by Andrew Theodore, senior director of Data Management and Analytics at AMN Healthcare (NYSE: AMN), the leader and innovator in talent solutions for healthcare organizations across the nation. Theodore will discuss how AMN used Infoworks DataFoundry to successfully migrate operational and financial forecasting production environments from Hadoop to Microsoft Azure Databricks.
“AMN has realized significant cost savings coupled with faster delivery of critical business intelligence,” said Russ Barck, Infoworks’ Vice President of Strategic Alliances. “A potent combination, particularly in a challenging environment. AMN is the leader in their industry in part because of smart, strategic investments such as DataFoundry, which is helping them realize the power of their data.”
Virtual Workshop: Unifying Data Pipelines, Business Analytics and Machine Learning with Apache Spark™
When: Wednesday, Sept. 2, 9 a.m. - noon PDT
9 a.m. – Databricks Keynote
9:45 a.m. – Customer Presentation: Andrew Theodore/AMN Healthcare
10:15 a.m. – Infoworks Partner Presentation
10:30 a.m. – Break
10:40 a.m. – Data Engineering Interactive Demo & Best Practices: Preparing Data for Analytics
11:15 a.m. – Data Science Interactive Demo & Best Practices: Model Training and Machine Learning
11:50 a.m. – Q&A
12 p.m. – Wrap Up
AMN Healthcare has used Infoworks DataFoundry to successfully migrate its operational 360 and financial forecasting production environments from Hadoop to Microsoft Azure Databricks in 6 weeks with zero downtime. Results included a 50% production operations costs savings while realizing a 25% decrease in analytics job execution times, delivering analytics agility to support business intelligence and data-based decision making. Infoworks DataFoundry for Databricks offers a best-in-class solution to improve analytics agility, increase operational efficiency and reduce dependence on costly and inefficient data operations infrastructure. It meets and exceeds the needs of modern companies embracing digital transformation.
Through automation, solution integration and abstraction away from the complexities of the underlying infrastructure, DataFoundry has established the data foundations for some of the world’s largest enterprises. Infoworks offers a highly optimized natively-integrated solution for customers that wish to onboard, prepare and operationalize data in Databricks Cloud environments. Infoworks DataFoundry enables data engineers, scientists, as well as business users up to the C-suite, to focus talent on solving problems while offloading manually intensive tasks to the highly automated, intuitive, drag-and-drop DataFoundry system. For additional information, please see: https://www.infoworks.io/datafoundry-for-databricks/. To experience the power of DataFoundry via a free test drive, please sign up here: https://go.infoworks.io/test-drive.
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Infoworks offers the most comprehensive and automated Enterprise Data Operations and Orchestration (EDO2) system. It is the only EDO2 system built to automate and accelerate deployment and orchestration of analytics projects at scale, in cloud, hybrid, multi-cloud, and premise-based environments. Through deep automation and a code-free environment, Infoworks empowers organizations to rapidly consolidate and organize enterprise data, create analytics workflows and deploy projects to production within days - dramatically increasing business agility and accelerating time-to-value. Infoworks counts some of the world’s largest financial, retail, technology, healthcare, oil & gas, and manufacturing companies as its customers. To learn more, please visit infoworks.io.
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