Data Management encompasses a vast range of tools, processes and techniques that aid an organization manage the vast amounts of data that it collects each day, while also making sure that its collection and use conform to all laws and regulations and current security standards. These best practices are vital for organizations who want to utilize data in a way that improves business processes, while reducing risk and enhancing productivity.

Often the term “Data Management” is often used interchangeably with terms such as Data Governance and Big Data Management, though most formalized definitions https://vdronlineblog.com/for-more-opportunities-with-board-room-software/ of this issue focus on how an organization manages its information assets and data from end to end. This includes the collection and storage of data, sharing and distributing of data as well as creating, updating and deleting data, and giving access to data analysis and application.

One of the most important aspects of Data Management is outlining a strategy for managing data prior to (for many funders) or in the early months following (EU funding) the research study starts. This is vital to ensure that scientific integrity is maintained and that the findings of the study are based on accurate and reliable data.

The difficulties of Data Management include ensuring that users can easily locate and access relevant information, particularly when the data is distributed across multiple storage locations in different formats. Tools that can connect disparate data sources are beneficial as are metadata-driven dictionaries and data lineage records which can reveal the origins of data from various sources. The data must be accessible to other researchers for reuse over time. This requires using interoperable formats such as.odt or.pdf instead of Microsoft Word document formats, and making sure that all the information needed is documented and recorded.