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Philanthropy Insight: Data Modelling
內容大綱
This exercise explores the operational and strategic challenges faced by Philanthropy Insight (PI), a Canadian non-profit organization founded by Emily Hayes, which aims to provide donors with information to make informed giving decisions. Despite significant growth in website traffic, PI struggles with chronic underfunding, leading Hayes to continually finance the deficit from her personal savings. The case delves into PI’s data management issues, including its use of disorganized and error-prone Excel spreadsheets, and looks at the potential value of structuring its data into a centralized database to better analyze donor behaviour and content effectiveness. Students are tasked with analyzing PI’s current data practices, understanding the implications of data structuring, and recommending strategies to improve operational efficiency and financial sustainability through better data management and analytics.
學習目標
The exercise focuses on the technical challenges of data modelling in non-profit organizations, particularly the transition from manual data processes to a centralized database. After working through the exercise and assignment questions, students should be able to:<ul><li>Analyze and develop a structured data model that captures the data elements and relationships necessary for Philanthropy Insight’s (PI) operations, including donor behaviors, charity profiles, and article engagement metrics.</li><li>Identify critical metrics for understanding donor engagement and content effectiveness, focusing on metrics such as website traffic, donation conversions, and donor retention.</li><li>Apply data analytics techniques to gain insights into donor behavior, optimize content strategy, and enhance PI's impact on philanthropic giving.</li><li>Evaluate the benefits and challenges of transitioning from spreadsheet records to a centralized database, including issues related to data migration, standardization, and staff adaptation.</li><li>Formulate strategic recommendations that utilize data-driven insights to support PI's long-term financial sustainability and operational efficiency.</li></ul>