Data Management data

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Data management comprises all the disciplines related to managing data as a valuable resource.

Overview[edit]

The official definition provided by DAMA International, the professional organization for those in the data management profession, is: "Data Resource Management is the development and execution of architectures, policies, practices and procedures that properly manage the full data lifecycle needs of an enterprise." This definition is fairly broad and encompasses a number of professions which may not have direct technical contact with lower-level aspects of data management, such as relational database management.

Alternatively, the definition provided in the DAMA Data Management Body of Knowledge (DAMA-DMBOK) is: "Data management is the development, execution and supervision of plans, policies, programs and practices that control, protect, deliver and enhance the value of data and information assets."

The concept of "Data Management" arose in the 1980s as technology moved from sequential processing (first cards, then tape) to random access processing. Since it was now technically possible to store a single fact in a single place and access that using random access disk, those suggesting that "Data Management" was more important than "Process Management" used arguments such as "a customer's home address is stored in 75 (or some other large number) places in our computer systems." During this period, random access processing was not competitively fast, so those suggesting "Process Management" was more important than "Data Management" used batch processing time as their primary argument. As applications moved more and more into real-time, interactive applications, it became obvious to most practitioners that both management processes were important. If the data was not well defined, the data would be mis-used in applications. If the process wasn't well defined, it was impossible to meet user needs.

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Q&A

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What is data cleaning in clinical data management?

Data cleaning is where the data may have missing data such as gender and the data manager has to go back to the source to find the data or data is incorrect and has to be corrected back at the source.

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How To Handle Data (Be a Data Manager) in a Clinical Trial

Clinical trials are facilitated to test the effectiveness and safety of a new drug. A clinical trial is a complicated procedure with equally complicated sets of data. These sets of data have to be competently managed and recorded to ensure that the clinical trial and the consequent study will derive an accurate and correct result. Handling data in a clinical trial is a laborious task. If you want to know how to do this, this article will show you how.