Self-Driving Data Management
As we mentioned in another glossary entry, data management involves working with data to ensure it is best suited for all needs within the organization. Self-driving data management takes data management a step further by making it more user-friendly, automated, and self-sufficient.
With AI and machine learning at its core, self-driving data management platforms understand user intent, pre-build solutions on the fly, and notify users of tasks that need their attention. The goal is to eliminate the tedious aspects of any data journey so that your company can focus on what’s important: creating value from your data.
Self-driving data management can use AI and metadata to translate your intents into fully-functional data management processes. Cataloging the system, monitoring data quality, cleansing data, and much more are all accessible once you communicate your goals into the system. It can find the right data sets and apply business rules to achieve your desired result. The platform can also guide you through complex governance tasks like creating the business glossary, managing reference data, or reviewing changes in PII.
In the past, most companies would reserve data management for data scientists, IT users, and people with the technical skills to work with data. They would need to spend most of their time assessing and working with data to make it available to everyone who needs it. As data becomes more universally used and appreciated, automated tools like self-driving data management will expedite this process. It will also make your data more accessible to everyone in your organization.