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Research Proposal 4.9

Data Quality And Bias in Impact Investing for Data Science Teams: Post-Pandemic Lessons

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Open Banking Cold Chain DevSecOps
Abstract

This research proposal investigates “Data Quality And Bias in Impact Investing for Data Science Teams: Post-Pandemic Lessons” using a survey-based structural equation modeling. Through a economic lens, the analysis integrates multi-source data to derive a stakeholder-aligned blueprint for researchers and practitioners.

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Data Quality And Bias in Impact Investing for Data Science Teams: Post-Pandemic Lessons

ABSTRACT
Data Quality And Bias in Impact Investing for Data Science Teams: Post-Pandemic Lessons is unpacked across themes: costs, benefits, interoperability, and change enablement. Limitations and future research paths are noted.
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