What Is Data Management?

Data management is an approach to the way businesses manage, store, and secure their data so it remains efficient and actionable. It also covers the methods and technologies that help achieve these goals.

The data that is used to run most companies is gathered from many different sources, compiled in various systems, and subsequently delivered in different formats. In the end, it is often difficult for data analysts and engineers to locate the correct data to perform their job. This results in unreliable data silos and inconsistent data sets, and other data quality issues which can hinder the effectiveness and accuracy of BI and Analytics applications.

A process for managing data improves visibility, reliability, as well as security. It also allows teams to better comprehend their customers and provide the most relevant content at the appropriate time. It’s important to start with clear objectives for data management and then develop a set of best practices that can be developed as the company grows.

For example, a good process should be able to handle both unstructured and structured 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 cleanse data. It should be flexible enough to adapt to the needs of any department’s workflow. Furthermore, it should be able try reading this to handle a variety of taxonomies and allow for the integration of machine learning. It should also be easy to use, and include integrated collaborative solutions and governance councils.

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