Data management is an approach to the way businesses gather, store and protect their data to ensure that it remains reliable and actionable. It also includes the techniques and tools https://taeglichedata.de/information-lifecycle-management-establishing-data-processes/ that support these goals.
The data that drives most companies comes from a variety of sources, is stored in numerous locations and systems, and is often delivered in various formats. This means it can be a challenge for engineers and data analysts to find the right information for their work. This can lead to unreliable data silos and inconsistent data sets, and other issues with data quality that limit the utility and accuracy of BI and Analytics applications.
A process for managing data can improve transparency, reliability and security while helping teams better understand their customers and provide the right content at the right time. It’s crucial to begin with clear business goals and then develop a set of best practices that will expand as the business expands.
A efficient process, for instance one that supports both structured data and unstructured in addition to sensors and batch workloads, while offering pre-defined business rules and accelerators, plus tools based on roles that aid in the analysis and prepare data. It should also be scalable and work with the workflow of every department. It should also be able to allow integration of machine learning and allow for different taxonomies. In addition it should be able to be accessed with built-in collaborative tools and governance councils for the consistency.