How to clean up messy data using Open Refine

How to clean up messy data using Open Refine

Open Refine describes itself as 'a power tool for working with messy data, cleaning it up, transforming it from one format into another, extending it with web services and linking it to databases like Freebase.'  It was borne out of a project started by Google (and used to be called Google Refine), but is now an open source project hosted on Github.

Read More

Four reasons why M&E software for large programmes fails

Four reasons why M&E software for large programmes fails

Government and NGOs don’t always have a great track record with technology projects.  Sadly this affects M&E systems as much as other areas.  However, it’s also clear that done well technology can make a big impact.  This may come in the form of cost savings (printing and transporting paper around), time savings (saving time spent transcribing data or manually aggregating data) and credibility (being able to quickly access and present data, aggregated at different levels with access to underlying evidence that backs it up).

Read More

How to prevent double counting

How to prevent double counting

Double counting can be one of the most problematic data quality issues in a development programme.  While it’s important not to lose sight of the bigger social change we are trying to create, this issue is at the heart of accurately measuring indicators that are important to many donors.  This blog post follows on from a previous post on data quality more generally.  It takes a practical look at how to prevent double counting and lists some ways in which others have avoided it.  It explores which of these options are best suited to your programme.

Read More

Improving data quality in your international development programme

Improving data quality in your international development programme

High quality data are important for NGOs and other's implementing international development projects.  Data are needed to plan new projects and programmes, evaluate and learn from existing ones and of course to be accountable to citizens and donors that you work with.  Collecting data without considering if it's of high quality undermines it's value as an ingredient in the decision making process.

Read More