Data management is broad term that encompasses many methods, tools, and techniques. These tools help organizations manage the huge amount of data they gather each day while also ensuring that their use and collection are in line with all laws regulations, rules, and current security standards. These best practices are crucial for organizations seeking to leverage data to enhance business processes while reducing risk and boosting productivity.
Often the term “Data Management” is often used interchangeably with terms like Data Governance and Big Data Management, however the most formal definitions of the topic concentrate on how an organisation manages data and information assets from beginning to end. This includes collecting and storing of data, delivering and sharing of data in the form of creating, updating, and deletion data and providing access to data for use in analytics and applications.
One of the most crucial aspects of Data Management is outlining a data management strategy before (for many funders) or in the early months after (EU funding) an investigation begins. This is vital to ensure that the integrity of the research is maintained and the results of the study are built on accurate and reliable data.
Data Management challenges include ensuring that users have the ability to locate and access relevant information, particularly when data is spread out across multiple systems and storage locations in various formats. Data such as dictionaries, data lineage records and other tools that integrate different sources of data are useful. Another issue is ensuring that the data is used for a long-term reuse by other researchers. This includes using interoperable formats such as.odt or.pdf instead of Microsoft Word document formats, and ensuring that all relevant information is documented and recorded.
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