What Is Data Management?

Data management is an approach to the way companies manage, store, and secure their data, ensuring that it remains efficient and actionable. It also covers the techniques and tools that support these goals.

The information that runs the majority of firms comes from various sources, and is stored in various locations and systems and is often presented in a variety of formats. As a result, it isn’t easy for data analysts and engineers to locate the correct data to complete their tasks. This leads to incompatible data silos in which data sets are inconsistent, as well as other data quality issues that may limit the usefulness of BI and analytics software and lead to faulty findings.

Data management can improve visibility and security, as well as helping teams better understand their customers and provide the appropriate content at the right time. It’s essential to begin with clear objectives for data management and then formulate a set of best practices that will develop as the business expands.

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

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