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What Is Data Management?
Data Management covers a broad variety of tools, processes and techniques that help an organization manage the vast amounts of data that it collects every day, while making sure that the collection and use comply with all laws and regulations, as well as up to date security standards. These best practices are vital for businesses looking to harness data in ways that can enhance business processes while reducing risk and boosting productivity.
Often, the term “Data Management” is used interchangeably with terms like Data Governance and Big Data Management however, the most formal definitions of the topic are focused on how a company manages information assets and data from beginning to end. This includes the collection and storage of data, delivering and sharing of data as well as creating, updating and deleting data, and providing access to data for analysis and application.
One of the most crucial aspects of Data Management is outlining a strategy for managing data prior to (for many funders) or in the initial months following (EU funding) a research study begins. This is crucial to ensure that the integrity of the research of the study is protected and that the study’s conclusions are based on reliable data.
Data Management challenges include ensuring that end users can locate and access the relevant information, particularly when data is spread out across multiple storage facilities in various formats. Data dictionaries, data lineage records and tools that combine disparate sources of data are useful. The data must also be available to other researchers for reuse in the future. This involves using interoperable file formats such as.odt and.pdf instead of Microsoft Word document formats and making sure that all the details needed to comprehend the data is gathered and documented.
