BrainBlog for JUXT by Eric Newcomer
Regulations and laws governing the collection and use of personal data are getting stricter every year. Penalties for infractions are growing, and becoming more and more common all the time.
A significant aspect of compliance is how the laws are enforced, and how organizations respond to issues, incidents, and breaches.
Internal audit teams are frequently tasked with ensuring the right controls are in place so that organizations avoid compliance and security issues. Regulators also frequently perform audits and checks to ensure organizations are implementing the correct safeguards.
And of course if an incident occurs, such as it often does, such as a public breach of customer data, consequences can be severe in terms of financial penalties and reputational impact.
Because databases are designed to work efficiently with disk, and transaction processing systems are designed to reflect the current state of the business, tracing the evolution of data values over time isn’t easy to program.
Resolving discrepancies in data governed by regulations and critical to risk calculations can take a lot of work. This would seem an obvious area for improved automation, such as what the bitemporal database, XTDB, provides.
