https://taeglichedata.de/information-lifecycle-management-establishing-data-processes/
Data management refers to the way businesses manage, store, and secure their data, ensuring that it remains efficient and actionable. It also covers the techniques and tools that support these goals.
The data that drives most companies comes from a variety of sources, and is stored in a variety of systems and places and is often presented in various formats. It can be difficult for engineers and data analysts to find the information they require for their job. This leads to disparate data silos, as well as inconsistent data sets, as well as other data quality problems that limit the utility and accuracy of BI and Analytics applications.
Data management processes improve visibility, reliability and security. It can also help teams better understand their customers and deliver the most relevant content at the appropriate time. It is crucial to establish specific data goals for the business and then develop best practices that will grow with the company.
A effective process, for example, should support both unstructured and structured data in addition to real-time, batch, and sensor/IoT workloads, and provide pre-defined business rules and accelerators. Additionally, it should offer tools based on roles that aid in the analysis and prepare data. It should also be scalable enough to be able to adapt to the workflow of any department. In addition, it must be able to accommodate a variety of taxonomies and allow for the integration of machine learning. Lastly, it should be accessible through built-in collaborative solutions as well as governance councils for coherence.
