Data management refers to the way businesses gather, store and protect their data, ensuring that it remains efficient and actionable. It also encompasses the technology and processes that support these goals.
Data that is used to run the majority of companies is gathered https://taeglichedata.de/information-lifecycle-management-establishing-data-processes from various sources, storing it in various systems, and delivered in different formats. This means it can be difficult for engineers and data analysts to find the appropriate data to carry out their tasks. This results in data silos that are not compatible in which data sets are inconsistent, as well as other issues with the quality of data which can hinder the use of BI and analytics software and result in inaccurate conclusions.
Data management processes improve transparency, reliability, and security. It also allows teams to better understand their customers and deliver the proper content at the right moment. It is crucial to establish clear goals for data management for the business, and then develop best practices that will develop with the business.
For instance, a great process should support both unstructured and structured data, in addition to batch, real-time and sensor/IoT-based workloads. It should also provide out-of-the accelerators and business rules as well as role-based self-service tools that help analyze, prepare and clean data. It should also be scalable and fit the workflow of any department. Furthermore, it should be able to handle different taxonomies as well as allow for the integration of machine learning. It should also be easy to use, with integrated collaborative solutions and governance councils.