The Importance of Data Management

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Businesses are now able to collect, analyze, and then monetize data in greater amounts than ever before. This gives them an edge. To tap into this goldmine, companies must adhere to the best practices in managing data. This involves the collection of data and its storage, as well as the governance across the company. In addition many applications that are based on data require high levels of performance and scale to provide the necessary insights to be successful.

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, while big data environments must be able to handle very massive volumes of unstructured and structured data in real-time. These applications might not function in their best capacity or provide inconsistencies and inaccurate results without an established foundation.

Data management is a combination of various disciplines that work together in order to streamline processes and improve communication. Teams typically include data architects, database administrators (DBAs), ETL developers, data analysts and engineers and data modelers. Some larger organizations employ master data managers to provide one point of reference for business entities such as vendors, customers and clients.

Effective data management also requires creating a culture of data-driven decision-making and providing the necessary training and resources to ensure that employees feel comfortable with making informed, data-based choices. Effective governance programs, such as clear requirements for data quality and compliance are another essential element of the successful strategy of managing data.

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