https://taeglichedata.de/pflege-von-datenprozessen-nach-sitzungssaal/
Data management is a strategy to the way companies gather, store and protect their data to ensure it is efficient and actionable. It also includes the tools and processes that help achieve these goals.
The information that runs the majority of companies comes from diverse sources, is stored in numerous locations and systems, and is often delivered in different formats. It is often difficult for engineers and analysts to locate the data they require for their work. This leads to incompatible data silos and inconsistent data sets, in addition to other issues with data quality that can limit the usefulness and accuracy of BI and Analytics applications.
Data management can increase visibility security, reliability and reliability while enabling teams to better know their customers better and provide the right content at right time. It’s essential to begin with clear business data goals and then develop a set of best practices that will grow as the company grows.
For instance, a great process should accommodate both unstructured and structured data in addition to real-time, batch and sensor/IoT-based workloads. It should also provide out-of-the accelerators and business rules as well as self-service tools based on roles that allow you to analyze, prepare and clean data. It must also be scalable and work with the workflow of every department. Furthermore, it should be able to handle a variety of taxonomies and allow for the integration of machine learning. It should also be easy to use, with integrated collaborative solutions and governance councils.