Data Analytics in Foundations Glossary of Terms

 

Data collection: The gathering, aggregating, and measuring information on targeted variables in a systematic fashion

Data analysis: The process of inspecting, cleansing, transforming, and modeling data to gain insights through pattern detection

Data management: The processes involved in acquiring, validating, storing, protecting, and processing data to ensure the reliability of data for users

Metrics:  The quantitative data points to which financial values can be applied and impact can be calculated

Impact: Measure of the tangible and intangible effects of influence on an individual or system

Economic impact: The effect that an impact will have on the economy. Economic impact analysis measures the difference between two events: if an event occurs and if an event does not occur. Economic impact in terms of social impact often captures both tangible and intangible impact.

Social value: The quantification of the relative value placed on different intangible aspects of society. Some social values are captured in market prices; other values must be inferred from existing data.

Tangible impact: A quantifiable impact related to an identifiable source or outcome.

Intangible impact: An unquantifiable impact relating to an identifiable source. While no firm value can be applied, often intangible impacts will be estimated.

Social Return on Investment (SROI): An economics-based performance measure that captures social impact by translating outcomes into financial values. SROI captures both the financial and social impact of an intervention.

Charitable ROI: Charitable ROI is an SROI measure used to calculate the potential social benefits resulting from a grant.

Relentless Monetization: A method of impact calculation where every effort is made to attach a financial value to program impacts to help determine the most successful programs

Predictive modeling: The process of creating, testing, and validating a model to best predict the probability of an outcome. Modeling methods include statistics, machine learning, and artificial intelligence

Probability of Success: A score developed using predictive modeling to estimate the likelihood of a grant-funded project succeeding as planned

Donor segmentation: Grouping beneficiaries and donors into categories based on needs, interests, or other key variables

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