As a data person primarily, these are focus areas I would like to dive deeper into w.r.t animal shelter analytics. For context, check [[Fur & Figures - Navigating the World of Animal Shelter Analytics]] ### 1. **Understanding Stakeholder Needs** - Discuss the diverse needs of stakeholders in animal shelters, focusing on refining and specifying the data and insights required by each group. ### 2. **Developing a Comprehensive Data Stack** - Explore considerations for creating an efficient data stack, including: - The role and limitations of using spreadsheets. - Designing effective software solutions for shelters. - Comparing open source versus off-the-shelf Modern Data Stack (MDS) ([[Honest Thoughts about the Modern Data Stack]]) tooling. - Prioritising user experience with fast data retrieval and analysis. ### 3. **Addressing Data Quality Challenges** - Strategies for ensuring data integrity, such as: - Implementing data contracts. - Establishing a semantic layer for data consistency. ### 4. **Data Generation and Integration in Shelters** - Analyse the types of data generated by shelters and the potential challenges in integrating various data sources. ### 5. **Deep Dive into Shelter Metrics** - A thorough examination of key metrics used in shelter analytics and their implications. ### 6. **Designing Effective Data Models** - Guidelines for designing a database schema and data model tailored for shelter analytics. ### 7. **Quantifying Benefits of Data Implementation** - Assessing the tangible benefits of data management in shelters, including: - Monetary savings or gains. - Improvements in operational efficiency. - Impact on animal lives saved. ### 8. **Fostering a Community-Driven Approach** - Advocating for open data access and accountability, particularly crucial for non-profit organisations. ### 9. **Building an In-House Tech/Data Team** - Insights on establishing a dedicated tech or data team within a shelter, including key skills and attributes to look for. ### 10. **Cultivating a Data-Driven Shelter Culture** - Strategies to embed a data-driven culture in shelters, such as: - Engaging staff with fun data exercises. - Encouraging collective responsibility for data accuracy. - Implementing tests and alert systems to identify and correct bad data. ### 11. **Maximising Data Utility in Shelters** - Exploring practical use cases and applications of data in the day-to-day operations of animal shelters.