The Importance of Data Management
Businesses can now capture and analyze data in greater quantities than ever before. This gives them a competitive advantage. To make the most of this goldmine, companies need to adhere to the best methods of managing data. This process includes the Data Management collection of data as well as its storage and governance across the organisation. Many data-driven applications require high performance and scale to provide the necessary insights to succeed.
For example advanced analytics (like machine learning and generative AI) and IoT and Industrial IoT scenarios need vast quantities of data in order to function properly, and big data environments have to be able to handle very massive amounts of unstructured and structured data in real time. Without a solid foundation these applications might not achieve their full potential or generate inaccurate and inconsistent results.
Data management is a mix of several disciplines that work together in order to automate processes and improve communication. Teams usually comprise data architects, ETL developers, database administrators (DBAs) and data analysts, engineers, and data modelers. Certain larger organizations employ master data managers to provide a single source of reference for business entities like vendors, customers, and products.
Effective data management is about creating an environment that encourages data-driven decision-making and providing employees with the training and resources they need to be confident in making data-driven choices. A solid governance program, with clear requirements for data quality and compliance are another essential element of a successful data management strategy.
