Data management is the way companies store, collect and protect their data to ensure it remains reliable and usable. It also includes the https://taeglichedata.de/maintaining-data-processes-throughout-the-information-lifecycle/ tools and processes that help achieve these goals.
The data used to run most companies is gathered from a variety of sources, stored in multiple systems, and presented in various formats. As a result, it can be difficult for engineers and data analysts to find the appropriate data for their work. This creates incompatible data silos as well as inconsistent data sets and other data quality issues that may limit the usefulness of BI and analytics software and lead to incorrect conclusions.
A data management process can increase visibility and security, as well as enabling teams to better understand their customers and deliver the right content at right time. It’s essential to establish clear goals for data management for the company, and then establish best practices that can evolve with the company.
A good process, for example it should be able to handle both structured and unstructured data, as well as real-time, batch, and sensor/IoT workloads, while offering pre-defined business rules and accelerators, plus tools that can be used to analyze and prepare data. It should also be scalable enough to be able to adapt to the workflow of any department. It must also be flexible enough to allow machine learning integration and to accommodate various taxonomies. It should also be easy to use, with integrated solutions for collaboration and governance councils.