Data Management encompasses a vast range of processes, tools and techniques that help an organization organize the massive amounts of data it collects each day, while also making sure its use and collection conform to all laws and regulations as well as up to date security standards. These best practices are vital for companies that wish to use data in a manner that improves business processes while reducing risk and increasing productivity.
Often the term «Data Management» is often used interchangeably with terms such as Data Governance and Big Data Management, however the most formalized definitions of this subject concentrate on how an organisation manages data and information assets www.vdronlineblog.com from beginning to end. This encapsulates the collection and storage of data; sharing and distributing data in the form of creating, updating and deleting data; and giving access to the data to use in applications and analytics processes.
Data Management is a vital element of any research study. This can be accomplished before the study starts (for many funders) or within the first few months (for EU funding). This is crucial to ensure that scientific integrity is maintained and that the findings of the study are founded on reliable and accurate data.
Data Management challenges include ensuring that end users can locate and access relevant information, particularly when data is spread out across multiple systems and storage locations in various formats. Tools that connect disparate data sources are beneficial and so are metadata-driven data dictionaries and data lineage records which can reveal how the data came from various sources. Another concern is ensuring the data is made available for long-term re-use by other researchers. This involves using interoperable formats such as.odt or.pdf instead Microsoft Word document formats, and ensuring that all information is recorded and documented.