Data management is the way companies store, collect, and secure their data to ensure that it remains reliable and usable. It also encompasses the processes and technologies that support these goals.
The information that runs the majority of businesses comes from multiple sources, is stored in many different systems and places and is often presented in different formats. This means it isn’t easy for engineers and data analysts to find the appropriate data to complete their tasks. This results in incompatible data silos and inconsistent data sets, and other issues with the quality of data that can limit the usefulness and accuracy of BI and Analytics applications.
A data management process improves transparency, reliability, and security. It also allows teams to better understand their customers and deliver https://taeglichedata.de/maintaining-data-processes-throughout-the-information-lifecycle/ the proper content at the right moment. It is essential to establish clear goals for data management for the company and then establish best practices that will grow with the company.
For instance, a successful process should support both structured and unstructured data–in addition to batch, real-time and sensor/IoT-based workloads. It should also provide out-of-the business rules and accelerators plus self-service tools for roles that assist analyze, prepare and clean data. It should be scalable to fit any department’s workflow. Furthermore, it should be flexible enough to accommodate different taxonomies and allow for the integration of machine learning. It should also be simple to use, and include integrated solutions for collaboration and governance councils.