Speed and Scale: Advanced Analytics with Machine Learning

Data engineering, the discipline of integrating, conforming, and readying data for downstream analysis, has been with us for many years, but it has new relevance and criticality today.  Data engineering has to support analytics, machine learning, and maintain data quality; and it must ensure data privacy, security, and protection of sensitive data, for compliance with GDPR and other regulatory frameworks.

A great data engineering platform must support full-fledged and operationalized data pipelines, be cloud-capable, and run on modern, distributed data execution platforms like Apache Spark. Finally, a modern data engineering platform must support savvy business analysts and other “citizen data engineers” – in addition to the more technical level database engineers, operators, and administrators.

That’s a long list of requirements, but it is readily attainable with today’s technology. To learn more, watch speakers from GigaOm, Talend and Databricks for this free 1-hour on-demand webinar from GigaOm Research.  The on-demand webinar features GigaOm analyst Andrew Brust, Mike Destein from Talend, and Brian Dirking from Databricks, focused on Apache Spark-based machine learning and data engineering.

In this 1-hour on-demand webinar, you will discover:

  • How modern data engineering platforms and cloud-based data processing services can work hand-in-hand
  • Why data engineering platforms must serve coders, architects, and analysts
  • How to facilitate self-service analytics and meet your data quality, privacy, security, and protection needs

To view this On Demand Webinar, please fill out the form.

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