What Is Data Management?

Data management is a strategy to the way companies manage, store, and secure their data to ensure that it remains efficient and actionable. It also encompasses methods and technologies that help achieve these goals.

Data that is used to run the majority of companies is gathered from a variety of sources, storing it in various systems, and then delivered in various formats. In the end, it can be difficult for engineers and data analysts to find the right information to carry out their tasks. This leads to disparate data silos, as well as inconsistent data sets, and other data quality problems which can hinder the effectiveness and accuracy of BI and Analytics applications.

A data management system can increase visibility and security as well as reliability, enabling teams to better understand their customers and deliver the right content at the appropriate time. It is essential to begin with clear business data goals and then come up with a list of best practices that can grow as the company grows.

A good process, for example one that supports both structured and unstructured and also sensors, real-time, batch and IoT workloads, while offering pre-defined business rules and accelerators, as well as tools based on roles that aid in the analysis and prepare 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 accommodate different taxonomies. In addition it should be accessible via built-in collaborative solutions and governance councils for the consistency.


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