As organizations try to keep up with new data types and become more advanced analytically, they must evolve and improve their data management practices.
Numerous interrelated factors contribute to the current state of data management. Many organizations are trying to unify their data for analysis, which may include a logical or physical architecture. Some enterprises are using cloud data stacks to store and manage their data; others are using a data fabric to stitch data together across multiple environments. Some are hiring CDOs or implementing DataOps to handle complex data pipelines.
Modern data management tools include augmented and automated capabilities. However, it will take work to get these tools to be widely used and maintained. Mature data management is still a work in progress for most organizations.
This State of Data Management Report examines the current state of data management, the top challenges organizations face, and best practices for your success.