Manage Data Management
Data has risen in importance for international cooperation, as development organizations are feeling the pressure to capture quantifiable evidence of social impact but also to predict and make informed decisions. The desire to become data-driven is not new for nonprofits. For instance The Guardian reminds us that, in 1858, a data visualization designed by social reformer Florence Nightingale demonstrated the importance of hygienic camps and hospitals with a diagram that showed that the main cause of mortality in the Army during the Crimean war was sickness, rather than wounds. Although nonprofits are well positioned to transform data into insights and social change, they don’t always have the means or knowledge to collect, aggregate and analyse meaningful data in a limited time. Luckily data has become an abundant resource and there are now many open repositories that collect relevant datasets for development cooperation projects in machine-readable formats.
Monitoring is an important task in the life of a programme or project. It involves regular and systematic assessment based on participation, reflection, feedback, data collection, analysis of actual performance (using indicators) and regular reporting. Monitoring makes it possible to gauge where programmes stand in terms of international norms and standards. It helps the Donors to understand where programmes are in relationship to results planned, to track progress (on the basis of intended results and agreed indicators), and to identify issues and analyze relevant information and reports that become available as implementation occurs. The Donors also monitor to fulfill accountability requirements; communicate, review and report results to stakeholders; adjust approaches to implementation if necessary; and inform decision-making. Monitoring feeds into evaluation and real-time learning.
The idea for this course comes from Gnucoop's many years of experience in Data Management.
From the Theory of Change, to the identification of Indicators, from the drafting of forms to the choice of the tool for digital data collection, to how to improve their use and how artificial intelligence can come to our aid.
to create figures able to make the best use of the data in their possession to enhance the effectiveness and efficiency of humanitarian projects.
Specifically, the path will consist of the following modules:
- Data management
- Data analysis I
- Data analysis II
- Impact measurement
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