The process of data management transforms raw information from disparate sources into a format that is ready to be stored, analyzed and integrated into business intelligence. It involves the identification and classification of data values performing the transformation, then moving and validating the newly created data before it’s ready for use.
This is crucial because it allows businesses to get the most out of their data. It allows them to eliminate problems with data quality and makes it easier for BI tools to work with the data. It makes managing data easier, reducing the number formats required for each kind of analysis and standardizing the formats.
It’s a crucial aspect of digital transformation, as it encourages organizations to treat their data as an asset, which requires to be monitored and measured, and matched with the company’s goals and objectives. The right data management practices will help companies identify new opportunities, improve efficiency and be more competitive.
Without a solid foundation of data However, it could be difficult to achieve the desired outcomes of a digital transformation. For example, machine learning and advanced analytics require large amounts of high-quality data in order for proper operation. And to be successful these technologies must be capable of processing and analyzing data in real-time. It’s crucial to understand how to connect your data and build a complete modern, modern architecture. Learn more about our latest O’Reilly eBook to learn how to do exactly that. It will teach you how to create one source of truth across all your data, enable mobile and remote workers, connect IT with the business and much more.