Data management is the practice of sectioning and arranging data files in a sensible and easy to navigate manner. This enables staff to locate straight from the source the information they require quickly and easily, while making sure that important information is not lost due to misplacement or unsuitable storage. Idealy, each file should be clearly linked to other files in the same folder, as well in relation to the overall objective of the research. This is usually achieved with a simple and clear file structure with subfolders. A readme file at the top of the folder is usually useful in guiding researchers to the structure.
The implementation of a successful data management strategy is vital for businesses to keep pace with the competition and ensure that their data is accurate, clear and current. Recent studies have shown that businesses that are driven by data and guided by data consistently outperform less knowledgeable competitors.
A solid plan for managing data begins by identifying the most important business objectives and mapping the process required to reach them. The plan should comprise tools, processes and governance, among other things. Organizations should also consider the appointment of accountable people to oversee the data management process and make sure that all employees have access to relevant data. The most successful plans for managing data take into account all the different aspects that includes both structured and unstructured data assets, that are used in today’s big-data systems. This includes cloud and on-premise data repositories. This can range from clickstream records and sensor data to transactional and shipping tracking points.
