Metadata is essential for managing, migrating, accessing, and deploying a big data solution. Without it, enterprises have limited visibility into the data itself and cannot trust in its quality—negating the value of data in the first place. Creating end-to-end data visibility allows you to keep track of data, enable search and query across big data systems, safeguards your data, and reduces risk.
In this O'Reilly webcast replay, Ben Sharma (co-founder and CEO of Zaloni) and Vikram Sreekanti (software engineer in the AMPLab at UC Berkeley) discuss the value of collecting and analyzing metadata, and its potential to impact your big data solution and your business.
Learning how to access to your data's lineage allows you to know where data has come from, where it is, and how it is being used. This webinar takes a deep dive into a new open-source project under development at UC Berkeley — Ground. Ground is a data context system that enables users to uncover what data they have, where the data is flowing to and from, who is using the data, and when and how it changes. We explore how data context stretches the bounds of what we have traditionally considered metadata.
Topics covered include:
- The role of metadata in data analysis
- Key considerations for managing metadata
- How to establish data lineage and provenance, in order to create a repeatable process
- How Ground is making an impact on a wide range of data tasks, including data inventory, usage tracking, model-specific interpretation, reproducibility, interoperability, and collective governance
- Initial work on Ground, and how this data context system is making an impact on a wide range of data tasks, including: data inventory, usage tracking, model-specific interpretation, reproducibility, interoperability, and collective governance