Big Data Management Best Practices for Data Lakes
TDWI Speaker: Philip Russom, TDWI Research Director
Date: Thursday, October 27, 2016
Time: 9:00 a.m. PT, 12:00 p.m. ET
Organizations are pursuing data lakes in a fury. Organizations in many industries are attempting to deploy data lakes for a variety of purposes, including the persistence of raw detailed source data, data landing and staging, continuous ingestion, archiving analytic data, broad exploration of data, data prep, the capture of big data, and the augmentation of data warehouse environments. These general design patterns are being applied to industry and departmental domain specific solutions, namely marketing data lakes, sales performance data lakes, healthcare data lakes, and financial fraud data lakes.
But despite the promise of data lakes, organizations continue to struggle to get value from them without best practices fully disseminated across user organizations. Leading organizations have begun to learn about how data lakes should be designed and managed, how they should be optimized for big data and specific applications, and how they fit into enterprise data ecosystems and architectures.
Join this webinar to learn about data management best practices, relative to big data and data lakes:
- How to design data lakes for both multi-purpose and single-purpose
- How metadata management makes a data lake more compliant and more trusted
- How data-driven self-service tasks can help achieve a data lake’s business goals
- How data governance prevents a data lake from becoming a data swamp
- How a hybrid data ecosystem is unified through a big data supply chain