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What Is Data Management?

Data management is a strategy to how businesses collect, store and protect their data to ensure that it remains efficient and actionable. It also covers the methods and technologies that help achieve these goals.

The information used to run the majority of companies is gathered from many different sources, compiled in various systems, and delivered in various formats. It is often difficult for engineers and data analysts to locate the data they require for their job. This can lead to unreliable data silos and inconsistent data sets, and other data quality problems that could limit the use and accuracy of BI and Analytics applications.

A data management process improves visibility, reliability and security. It helps teams better comprehend the needs of customers and provide correct content at the right time. It is essential to establish clear goals for data management for the company, and then devise best practices that can evolve with the company.

For example, a good process should accommodate both structured and unstructured data–in addition to real-time, batch and sensor/IoT tasks. In addition, it should provide out of the box accelerators and business rules as well as self-service tools for roles that assist analyze, prepare and clean data. It should also be scalable enough to work with the workflow of every department. It should also be able to allow machine learning integration and allow for different taxonomies. It should also be easy to use, with integrated collaboration solutions and governance councils.


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