Data Management encompasses a wide range of tools, processes and techniques that help an organization organize the huge amounts of data that it collects every day, while making sure that the collection and use adhere to all laws and regulations as well as up to date security standards. These best practices are essential for organizations who want to utilize data in a manner that improves business processes, while reducing risk and enhancing productivity.
The term “Data Management”, which is often used in conjunction with Data Governance and Big Data Management (though the most formal definitions focus on how an organization manages its information and data assets end-to-end), encompasses all of these actions. This encapsulates the collection and storage of data; sharing and delivering data in the form of creating, updating and deleting data; and providing access to the data for use in applications and analytics processes.
Data Management is a vital element of any research study. This can be done prior to the beginning of the study (for many funders), or within the first few months (for EU funding). This is essential to ensure that the scientific integrity of the study is preserved and to ensure that the study’s findings are based on accurate data.
The challenges of Data Management include ensuring that users can easily locate and access relevant data, especially when the data is spread across multiple storage locations with different formats. Data dictionary, data lineage records and tools that connect disparate sources of information are beneficial. Another challenge is ensuring that the data can https://vdronlineblog.com/how-to-seamlessly-move-and-manage-data-in-the-cloud-with-virtual-data-rooms/ be made available for long-term re-use by other researchers. This requires using interoperable formats such as.odt or.pdf instead Microsoft Word document formats, and ensuring that all relevant information is captured and documented.