Data Engineering with StreamSets DataOps Platform

Agenda:
6:30 pm - Pizza and networking
7:00 pm - Welcome, announcements, and job openings
7:10 pm - Introduction to StreamSets and Transformer, Transformer Extensibility, and Q&A

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Data Engineering with StreamSets DataOps Platform

StreamSets Transformer is an execution engine within the StreamSets DataOps platform that allows users to create data processing pipelines that execute on Spark. Using a simple to use drag and drop UI users can create pipelines for performing ETL, stream processing and machine learning operations. It allows everyone, not just the savvy Spark developers, but also the Data Analysts, Data Scientists or legacy ETL developers to fully utilize the power of Apache Spark without requiring a deep technical understanding of the platform with minimal operational and configuration overhead.

StreamSets Transformer pipelines are heavily instrumented and provide deep visibility into the execution of Spark applications. Users can see exactly how long every operation takes, how much data gets transferred at every stage, and view proactive and contextual error messages if and when problems occur. These features add an abstraction layer on top of the internals of Apache Spark and allow data engineers to focus on solving the core business problem.

Speaker Bios:

Dan Matic, StreamSets Regional Sales Director for 2 years, has been an Enterprise Software Sales Executive for 30+ years. Before StreamSets, Dan spent over 10 years at DataFlux/SAS in their Data Management division. His specialty is data integration with previous experience at vendors like Informatica where he was the first sales rep in the Midwest in 1996, landing several of Informatica's first paying customers, helping Informatica grow from zero to 12 million in revenue in its first 18 months. Dan is a graduate of Lawrence University, Appleton, WI with a BA in Mathematics.

Adam Bracey, StreamSets Solutions Engineer, has been in the Data Integration space for the past 18 years. Before StreamSets, Adam spent over 10 years at Informatica architecting and implementing Data Integration solutions around Big Data and Cloud ecosystems as well as traditional Data Warehousing. Adam is a graduate of the University of Kentucky with a BA in Computer Science.

Dash Desai, StreamSets Platform Evangelist, has 15+ years of hands-on software and data engineering background. With his recent experience in Big Data, Data Science, and Machine Learning, Dash is able to apply technical skills to help build solutions that solve business problems and surface trends that shape markets in new ways. As a platform and technical evangelist, he is passionate about evaluating new ideas and help articulate how technology can address a given business problem. Dash has worked for global enterprises and in agile environments for tech startups in the Bay Area in varying verticals, such as VoIP, Online Gaming, Digital Health, NoSQL database, and Big Data platforms.

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