Let’s say you want to share information with another company. There could be a wide variety of valid reasons to share information, such as sending inventory information to place an order from a vendor or report production details to support an external production audit. Let’s also say you plan to send thousands of pieces of data in the exchange.
Here’s the problem: Once the data is out of your control, you can no longer assume that it’s leveraged and secured according to the data policies of the company. The data is now decoupled from your data management control plan and no longer has a reference to its structure, purpose, data governance, and, of course, its data security.
You run a high risk that someone will leverage your data in ways that you and/or your enterprise would not approve. There could be unintended accidents such as a leak of data that should be private or purposeful misuse such as selling the data to an investor who wants to leverage the data for insider trading.
But what if your data could take all its attributes and policies along on this journey? Attributes could include valid use cases, security, and governance, and a log that tells exactly how the data is leveraged as it’s leveraged. In other words, the data would have the ability to protect and manage itself. You would be assured that the data will be used in approved ways and never fall outside of those approved parameters. Would that be of value to you?
If you Google “autonomous data,” you’ll end up with many different definitions. It’s a topic that’s been part of many Ph.D. dissertations over the years. It’s also a regular topic of conversation in the halls of database vendors, large and small. However, the autonomous data that’s coming soon will be a bit different from the structured and unstructured data of the present and past.
Here are three common attributes that will set autonomous data apart:
1. The ability to self-manage when decoupled from a database. Autonomous data is surrounded by small, decoupled data management layers that can live on many different platforms and manage the data by using a distributed model. The autonomous data can still maintain a connection back to a database control plane, but that control plane can work across many different clouds, applications, users and even exist inside other databases.
2. Support for structured and unstructured data using the same mechanisms.Since the control plane applies structured at the time of use, to either unstructured data or structured data that you would like to leverage differently, you can leverage this technology for both structured and unstructured data without having to reconfigure.
