Challenges and Best Practices for Reducing Your Data Risk Footprint
Data in non-production environments occupy a significant percentage of total enterprise data volume--often as much as 80%. Non-production environments also carry more risk than production because there are more direct users. Data security regulations such as GDPR, CCPA, NY DFS etc., do not distinguish between non-production and production environments. If the data is real, it is within regulatory scope. Understanding the risks and how to protect these environments initially and on-going with process efficiency is very challenging.
In this session, we will discuss the challenges, architectural patterns, and process improvements to make data protection in non-production environments feasible:
- How to deal with integrated data environments where data needs to be protected consistently and potentially across different types of data sources
- How to deal with data sets which are located on-prem, in public cloud, and/or in other countries sometimes held by partners
- How to do this at scale for ever increasing data volumes with a workforce rarely all located in the same place, let alone the same country