Data Resource Management is the development and execution of architectures, policies, practices and procedures that properly manage the full data lifecycle needs of an organization. This includes data processing, data research and a host of other solutions.
Data management in clinical research relates to the processes of gathering, recording, monitoring, analysing and reporting on data.
Our application development services consist of a wide range of solutions, which includes complex Business Intelligence applications, Portals, Content Management and Data Management and Architecture.
Topics in Data Management include:
- Data modelling.
- Database administration.
- Data warehousing.
- Data movement.
- Data mining.
- Data quality assurance.
- Data security.
- Meta-data management (data repositories, and their management).
- Data architecture.
Data management becomes even more challenging when there are fusions and acquisitions and multiple data sets need to be consolidated.
There several challenges are positioned like poor data quality, incompatibilities between data sets, duplication of data and outflows in multiple systems.
Thus, second phase of IT evolution is directed at simplifying the information landscape of the enterprise.
Master data management is a tactic to standardise data comprising tools and technologies for classifying, normalising, consolidating and aggregating data across the enterprise to provide a consistent view.
The process of data management should be ongoing and should begin at the early stages of protocol development, and end only when statistical analysis is complete.