Data management is the process of controlling the information generated during a research project. Data management incorporates all parts of data planning, handling, analysis, documentation and storage. It takes place amid all phases of a study. The goal is to make a solid information base constituting high quality data. The process of Data managementincludes the following steps:

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  • Planning the data needs of the study
  • Data collection
  • Data entry
  • Data validation and checking
  • Data manipulation
  • Data files backup
  • Data documentation

Each of these procedures requires thought, time and meticulous attention.

The fundamental component of data management is database documents. Database files contain content, numerical, images and other information in machine intelligible structure. Such records ought to be seen as a feature of Data Base Management Systems (DBMS) which takes into account a broad range of data functions, including data entry, checking, updating, documentation and analysis.


Data Base Management Systems (DBMS) are available for personal computers such as Spread sheet in Excel, SPSS datasheet; Commercial database program in Oracle, Access; Specialty data entry program in SPSS Data Entry Builder, EpiData. Spread sheets are to be avoided as they are unreliable and easily get corrupted. Commercially available database programs are expensive. They tend to be large and slow and often lack controlled data-entry facilities. Specialty data entry programs are ideal for data entry and storage. EpiData is used for this purpose because it is fast, reliable, allows for controlled data-entry and is open-source.

There are many errors that occur after the data have been collected. Transpositions, Coding errors, Consistency errors, Copying errors, Routing errors, Range errors are examples of these data processing errors. It is necessary to acknowledge the stage at which these errors occur in order to prevent them. Manual checks during data collection, range and consistency checks during data entry, double entry and validation following data entry, data analysis screening for outliers during data analysis are methods to prevent data entry errors.

Share Info Systems Pvt Ltd provides you information on your fingertip. It helps you manage the various data from various sources and proactively govern the data to make sure that information is complete. This ultimately results in smarter decision-making.

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