Data management is a method to the way companies manage, store, and secure their data so it remains reliable and actionable. It also encompasses the technologies and processes that support these goals.
The data that runs most companies comes from a variety of sources, and is stored in various locations and systems and is often presented in a variety of formats. It is often difficult for engineers and data analysts to locate the data they need for their work. This results in discordant data silos and incompatible data sets, in addition to other data quality problems that could limit the use and accuracy of BI and Analytics applications.
A process for managing data improves visibility, reliability and security. It helps teams better understand their customers and deliver the appropriate content at the right moment. It’s crucial to begin with clear business goals and then come up with a list of https://taeglichedata.de/information-lifecycle-management-establishing-data-processes best practices that will expand as the business grows.
A effective process, for example will be able to accommodate both structured and unstructured in addition to real-time, batch, and sensor/IoT workloads, and provide pre-defined business rules and accelerators. It should also include tools based on roles that aid in the analysis and prepare data. It should also be scalable and be able to adapt to the workflow of any department. In addition, it should be able to handle a variety of taxonomies and allow for the integration of machine learning. Lastly it should be able to be accessed with built-in collaborative solutions and governance councils to ensure coherence.