Postrevolutionary big data: Promoting the general welfare (sponsored by Io-Tahoe)
Data democratization was a chief goal and major benefit of the big data revolution. Data owners no longer have to wait for the EDW IT Department to write ETL jobs before they can access and query their data. Anyone can store their data in the data lake, in any structure (or no consistent structure).
Ten years later, we’re struggling with the unintended consequences of the big data revolution. Data is often multiply redundantly stored. Data of interest is difficult to locate, and its schemas are often difficult to understand. Precise connections among putatively related datasets are not captured. The great promise of the big data revolution—integration of data across silos to discover otherwise hidden trends and improve customer experience— has largely gone unrealized due to this postrevolutionary chaos.
Barbara Eckman shares lessons learned from early big data mistakes and the progress her team at Comcast is making toward a postrevolutionary big data vision.
This keynote is sponsored by Io-Tahoe.
Barbara Eckman is a senior principal software architect at Comcast specializing in big data architecture and governance. She leads data discovery and lineage platform architecture for a division-wide initiative comprising streaming, transforming, storing, and analyzing big data. Barbara is also the lead metadata architect for the Comcast Privacy Program, an initiative tackling the challenge of legislation like the California Consumer Privacy Act. Her prior experience includes scientific data and model integration at the Human Genome Project, Merck, GlaxoSmithKline, and IBM, where she served on the peer-elected IBM Academy of Technology.
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