Key elements of data processing

  • Data processing software design and selection
  • Real-time reports
  • Data cleaning
  • Key indicators for checking captured data against historical data
  • Data entry (where physical data collection forms are used)

Data is ideally captured digitally in an EMIS in real-time, using software applications across decentralized platforms. These software applications may include the school management information systems, digital forms, data spreadsheets and mobile apps. Once this data is submitted by schools, district or regional offices, and other organizations that collect EMIS data, it needs to be checked for inaccuracies, cleaned, and transformed into structured formats so that it becomes part of the master data sets in the EMIS. This is called data processing. If physical data collection tools are used in an EMIS ecosystem, this data must be captured digitally and then processed.

Within the EMIS ecosystem, data processing is defined as:

The digital transformation (usually automated, but in some cases manual) of data from decentralized systems (at schools, district or regional offices, payroll divisions, and development partners) into formats for inclusion in EMIS master data sets.

Explore these essential ‘component’ resources:

  1. Education Management Information Systems (EMIS) A Guide for Young Managers – This guide provides a clear outline of data management in an EMIS.
  2. An overview of key data sets in education in South Africa – This paper provides an overview of the data sets and management for education in South Africa but is relevant to anyone with an interest in data management in an EMIS.
  3. Efficiency and Effectiveness in Choosing and Using an EMIS Guidelines for Data Management and Functionality in Education Management Information Systems (EMIS) – This guide comprises two main sections: a 'Buyer’s Guide' that refers to the standards of functionality a system ought to have, and a 'User’s Guide' that refers to how to make better use of an EMIS once a country has it. It is useful for understanding data processing.

Steps to effective data publication and dissemination in EMIS

  • Design or select software applications that support data processing:Software apps should translate collected data into compatible formats for the EMIS (for example, raw datasets in an Excel spreadsheet can be transformed into different types of interactive or visual reports and summaries using other software apps that can interact with Excel).
  • Ensure real-time reporting: Software apps and data processing performed by data clerks and users should have the functionality to generate real-time reports for checking.
  • Perform data cleaning:Check captured data for import errors. This may require proofreading of captured data, or analysis checks to make sure it is accurate. Use key indicators established for data checking to compare and check captured data against historical data.
  • Do data entry if necessary: This is only required if data has been collected using physical data collection forms. Data capturers need to be trained to capture data in the digital system, using the software apps.