What Is Data Management?

Data management refers to the way companies manage, store, and secure their data to ensure it is effective and reliable. It also includes the tools and processes that support these goals.

Data that is used to manage most businesses is gathered from many different sources, storing it in various systems, and delivered in different formats. It is often difficult for engineers and analysts to locate the data they need for their work. This results in incompatible data silos and inconsistent data sets, in addition to other data quality issues which can hinder the effectiveness and accuracy of BI and Analytics applications.

A process for managing data will improve the visibility security, reliability and reliability while helping teams better comprehend their customers and provide the right content at right time. It’s essential to establish specific data goals for the business, and then create best practices that will develop with the business.

For instance, a reputable process should be able to handle 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 that are based on roles to help analyze, prepare and cleanse data. It should also be scalable and adapt to the workflow of any department. It should also be flexible enough to allow integration of machine learning and support different taxonomies. Additionally it should be available with built-in collaborative solutions and governance councils for consistency.



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