What Is Data Management?

Data management is a method to the way businesses manage, store, and secure their data to ensure it is useful and actionable. It also encompasses the processes and technologies that support these goals.

Data that is used to run the majority of companies is gathered from multiple sources, storing it in various systems, and presented in various formats. Therefore, it is often difficult for engineers and data analysts to locate the correct data to complete their tasks. This can lead to incompatible data silos and inconsistent data sets, and other issues with the quality of data that can limit the usefulness and accuracy of BI and Analytics applications.

Data management processes improve visibility, reliability, as well as security. It can also help teams better understand customers and deliver the proper content maintaining data processes the information lifecycle at the right moment. It’s essential to establish specific data goals for the business, and then develop the best practices to develop with the business.

For instance, a successful process should accommodate both structured and unstructured data–in addition to real-time, batch, and sensor/IoT workloads–while offering out-of-the-box business rules and accelerators plus self-service tools for roles that assist analyze, prepare and clean data. It must also be scalable to be able to adapt to the workflow of any department. It must also be flexible enough to allow integration of machine learning and allow for different taxonomies. In addition it should be able to be accessed via built-in collaborative solutions and governance councils for consistency.