Companies are now able to capture, analyze, and then monetize data in greater quantities than ever before. This gives them a competitive advantage. However, to access this goldmine of information companies must follow established best practices for managing data. This includes the collection, storage and administration of data within an organization. In addition, many data-driven applications require an extremely high level of performance and scale to deliver the insights needed to succeed.
For instance advanced analytics (like machine learning and generative AI) and IoT and Industrial IoT scenarios need vast amounts of data to function properly, and big data environments have to be able to handle very large volumes of unstructured and structured data in real time. Without a solid foundation these applications can fail to perform at their highest www.vdronlineblog.com level or produce inconsistent and inaccurate results.
Data management is the combination of various disciplines working together to streamline processes and improve communication. Teams typically comprise data architects, database administrators (DBAs), ETL developers and engineers, data analysts and data modelers. Certain larger organizations employ master data management professionals to create an unifying source of reference for business entities like customers, products and vendors.
Effective data management involves creating a culture that encourages the use of data to make decisions and giving employees the education and resources they require to be confident in making decisions based on data. Solid governance programs, which contain clear data quality and regulations, are an essential component of any successful strategy for managing data.