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Improve Real-time Processing and Insight with a Hadoop Operational Data Lake

Duration: 60 minutes (including Q&A)

Hosted by Data Informed, sponsored by Splice Machine

If you have been following Big Data or Hadoop, you might have heard about the concept of the “data lake,” which collects data across multiple sources in their natural or unfiltered formats. You then “filter,” or process, that data as you use it. It sounds simple, but there’s a lot to it. This webcast will drill down into the business value a real-time operational data lake offers and the problems it solves.

Attend this webcast to:

• Learn how a real-time Operational Data Lake works as a subset of a Data Lake
• Understand how an operational data lake relates to operational data stores
• Gain methods to streamline and harden your ETL processing pipeline
• Get tips to use a data lake to create a unified customer profile for your digital marketing
• Find out how to enhance an existing Hadoop-based data lake
• Step through real-world use cases of how customers are applying data lakes to save time and money

Join Rich Reimer, VP of Product Management from Splice Machine to discuss specific case studies of how companies use operational data lakes to offload operational reporting from expensive OLTP and data warehouses and streamline their ETL processing pipelines.

Featured Speaker:

Rich Reimer, VP Product Management, Splice Machine

Rich has over 15 years of sales, marketing and management in high tech companies. In his role as VP of Product Management, Rich works with many of Splice Machine’s customers to define and implement data lakes and unified customer profiles. Most recently, Rich worked at Zynga where he used petabytes of data from millions of daily users to optimize the business in real time. Rich has a BSEE from University of Michigan, an MSEE from Columbia and an MBA from Harvard University.

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