Data Governance 101

Data compliance, privacy and security is hard because:
* There is too much data
* There is too much complexity
* There is no context to data usage.

Automation is the only hope.

This talk introduces the first steps to automate data governance tasks to answer:
* Where is my data ?
* Who has access to the data ?
* How is the data used ?

We will discuss data governance automation examples for AWS Redshift, Snowflake and MySQL from Tokern Data Governance projects (https://tokern.io) .
The information from these tasks will set the foundation for an effective strategy for compliance, privacy and security.

Transcript

1. Data Governance 101
2. Agenda • • ◦ ◦ ◦ • ◦ ◦ ◦ •
3. What is Data Governance? • • ◦ ◦ ◦
4. Why is Data Governance hard? • • •
5. There is too much data. • 1.7 megabytes every second, per person • 1/3 of all data cloud https://www.nodegraph.se/big-data-facts/ https://gawker.com/the-public-nyc-taxicab-database-that-accidentally-track-1646724546
6. There is too much complexity ~ 1500 Data Technologies >7000 Marketing Tech Companies >700 Sales Tech Companies
7. There is no context for data usage • • • • • •
8. Automation to ease data governance • • •
9. Where is my sensitive data? • • •
10. PIICatcher - Data Catalog of PII data https://github.com/tokern/piicatcher
11. Data Lineage to track sensitive data • • • https://github.com/tokern/data-lineage https://tokern.io/docs/data-lineage/example/
12. Who has access to sensitive data? 1 2 3
13. How is sensitive data used? • • • •
14. Query History in Snowflake
15. Query History for MySQL • • • https://tokern.io/blog/proxysql-database-audit/
16. Summary • • • • ◦ ◦ ◦ ◦ ◦