Without a solid plan, data management can be messy, expensive, and worst of all—ineffective. ... Here are four core principles of how to do it right: 1. Ask the right questions.

DAMA International’s Data Management Body of Knowledge is a framework specifically for data management. ... there are three core principles of data architecture: Scalability.

Metadata management: Here, AI and ML can be used to explore and define the data’s metadata, evaluating metadata faster and more accurately, with reduced redundancy.

Automation ensures that all core data management capabilities are embedded in the tools and experiences that enable users to work with data. Data ecosystems need to scale — especially in the AI era.

Data lifecycle management: Assists in maintaining data through various phases such as creation, validation, archival or retirement. Ensures that master data is up-to-date, relevant and aligned ...