Data management is the way businesses collect, store, and secure their data to ensure it is reliable and usable. It also encompasses the technology and processes that support these goals.
Data that is utilized to run a lot of businesses is gathered from many different sources, stored in multiple systems, and presented in different formats. As a result, it can be difficult for engineers and data analysts to locate the correct data to perform their job. This leads to incompatible data silos, data sets that are inconsistent and other issues with data quality that could limit the utility of BI and analytics software and lead to faulty findings.
A process for managing data can increase visibility and security as well as reliability, enabling teams to better understand their customers and provide the right content at right time. It’s important to start with clear goals for business data and then come up with a list of best practices that will develop as the business grows.
A good process, for example it should be able to handle both structured and unstructured data in addition to batch, real-time, sensor/IoT workloads, and provide pre-defined business rules and accelerators. Additionally, it should offer role-based tools to help analyze and prepare data. It should be scalable to meet the requirements of any department’s workflow. Additionally, it should be able to adapt to a variety of taxonomies and allow for the integration of machine learning. It should also be easy to use, with integrated solutions for collaboration and governance councils.
https://www.taeglichedata.de/master-data-management-the-first-steps-in-data-consolidation