What Is Data Management?

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Data management is the method by which businesses collect, store and secure their data to ensure that it remains safe and useful. It also encompasses the technology and processes that assist in achieving these goals.

The data that runs most companies comes from diverse sources, and is stored in various locations and systems, and is often delivered in different formats. This means it is often difficult for engineers and data analysts to locate the correct data to complete their tasks. This leads to unreliable data silos and inconsistent data sets, in addition to other data quality problems that could limit the use and accuracy of BI and Analytics applications.

Data management processes improve transparency, reliability, and security. It also allows teams to better comprehend the needs of customers and provide proper content at the right moment. It’s essential to establish clear data goals for the company, and then devise the best practices to develop with the business.

A effective process, for example one that supports both structured data and unstructured in addition to real-time, batch, and sensor/IoT workloads, and provide pre-defined business rules and accelerators, as well as role-based tools that help analyze and prepare data. It should be scalable to fit any department’s workflow. Additionally, it should be able to adapt to different taxonomies and allow for the integration of machine learning. In addition it should be available through built-in collaborative solutions as well as governance councils to ensure consistency.