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What Is Data Management?

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Data Management encompasses a broad variety of tools, processes and techniques that aid an organization organize the huge amounts of data that it collects each day, while also ensuring its collection and usage conform to all laws and regulations and up to date security standards. These best practices are vital for businesses looking to harness data to enhance business processes while reducing risks and enhancing productivity.

The term “Data Management”, which is often used to refer to Data Governance and Big Data Management (though most formalized definitions focus on the way an organization manages its data and other assets end-to-end) encompasses all of these activities. This includes collecting and storing of data, sharing and distributing of data, creating, updating and deleting data, and giving access to data for use in applications and analytics.

One of the most important aspects of Data Management is outlining a strategy for managing data before (for many funders) or in the initial months following (EU funding) the research study starts. This is essential to ensure that the scientific integrity of the research is maintained and that the study’s conclusions are based on accurate data.

Data Management challenges include ensuring that users have the ability to locate and access the relevant information, especially when data is spread out across multiple systems and storage locations in various formats. Tools that can connect disparate data sources are useful as are metadata-driven linesage records and dictionaries that show the source of the data from different sources. Another concern is making sure that the data can be used for a long-term reuse by other researchers. This involves using interoperable file formats such as.odt and.pdf instead of Microsoft Word document formats and making sure that all the information required to understand the data is recorded and documented.

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