"This open access book provides practical guidance for non-profits and community sector organisations about how to get started with data analytics projects using their own organisations' datasets and open public data. The book shares best practices on collaborative social data projects and methodology. For researchers, the work offers a playbook for partnering with community organisations in data projects for public good and gives worked examples of projects of various sizes and complexity." (Publisher description)

"By ‘data for social good’, we mean using contemporary data analytics techniques to fulfil a social mission or to address a social challenge. Data analytics is understood as the process of examining data to find patterns and insights that can aid decision-making and offer courses of action (Picciano, 2012). We define non-profits as all those organisations and community groups operating to pursue a social mission and that do not operate to make a profit. Individual non-profit organisations are thought of here as each pursuing their defined social mission, but also contributing to a collective social mission of achieving a more equitable and just society. While non-profits are often using data to track their operations and aid reporting, we emphasise the data that non-profits could use to further their work and goals. This includes mainly: a. internal data generated routinely from non-profits’ own operations or new data they might collect (e.g., to inform evaluation). Such data could be used, or re-used, for insights by individual non-profits or in data sharing collaboratives with other organisations and b. external open data generated through government agencies or made available by other organisations.
We take a pragmatic stance here as we write at a specific point in time and from our home country context (Australia), which we acknowledge is a high-income country with neoliberal ideology influencing social policy. Non-profit data analytics is a fast-moving field where practices and legislation will change. Other countries and regions have their own nuances. Globally, the non-profit sector is on a journey with data collection and computational data analytics. This is influenced by policy that drives competition and demand for accountability and measurement, as well as a desire to use sophisticated techniques for social good. This journey will continue into the future." (Introduction, page 2-3)