As organizations move onto Google Cloud platforms, there are three main concerns from Data Offices that hamper the flow of more data to the cloud. First, when data moves from its silo’s to a central data platform, ownership and accountability is an issue. Second, discovery of sensitive data. Data needs to be found, identified and the right policy needs to be applied so users can confidently, quickly and securely request access. Third and final, customers report a lot of risk in bad data.
In this session, experts from Google Cloud and Collibra share how to leverage ML to automate data quality rules – scan disparate and dynamic datasets, detect anomalies, discover sensitive data – all to improve the quality, accessibility, and governance of your data.
Additionally, the webinar reviews the core capabilities needed to unlock access to data and to derive value from that data. They include: