The digital age has allowed companies to collect, analyze and monetize more data than ever before, allowing companies the potential for a powerful competitive advantage. To tap into this goldmine, companies need to follow the best practices in data management. This includes the gathering, storage and management of data throughout an company. Many of the applications that use data require high-performance and scale in order to provide the insights required to be successful.
For instance, advanced analytics like machine learning and generative AI as well as IoT and Industrial IoT situations require vast amounts of data in order to function effectively. Big data environments must be able to handle massive volumes structured and unstructured information in real time. These applications may not perform optimally or deliver inconsistent and inaccurate results if they do not have the right foundation.
Data management encompasses a range of disciplines that collaborate to automatize processes, improve communication and speed up delivery of data. Teams typically include data architects, database administrators (DBAs), ETL developers Data analysts, engineers, and data modelers. Some larger companies employ master data management experts to create one point of reference for business entities such as vendors, customers, and products.
Effective data management involves creating a culture of data-driven decisions and providing training and resources to make sure that employees feel comfortable making informed, based decisions. Solid governance programs, which include clear requirements for data quality and compliance are another essential element of a successful data management strategy.