What Is Data Management?

Data management refers to how businesses manage, store, and secure their data so it remains useful and actionable. It also includes the techniques and tools that support these goals.

The information that runs the majority of businesses comes from multiple sources, and is stored in many different systems and places and is typically delivered in various formats. It is often difficult for engineers and analysts to find the information they require information lifecycle management for their work. This results in data silos that are not compatible in which data sets are inconsistent, as well as other issues with data quality that may limit the usefulness of BI and analytics applications and lead to incorrect conclusions.

A process for managing data can improve transparency and security, as well as allowing teams to better understand their customers and deliver the appropriate content at the right time. It’s important to start with clear business data goals and then formulate a set of best practices that will develop as the business grows.

A good process, like, should support both structured and unstructured data, as well as sensors, real-time, batch and IoT workloads, and provide pre-defined business rules and accelerators. Additionally, it should offer role-based tools that help analyze and prepare data. It should be scalable enough to meet the requirements of any department’s workflow. In addition, it must be able to handle various taxonomies and allow for the integration of machine learning. It should also be simple to use, with integrated collaboration solutions and governance councils.

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