Data Quality Governance: Overview, Challenges, and Practices
This presentation by Zhou Jie, a senior data R&D expert at Ant Financial, outlines the scope of data governance, examines the challenges of ensuring high‑quality financial data, and shares practical architectures, solutions, and case studies to help attendees understand data quality risks and mitigation strategies.
Speaker: Zhou Jie, Senior Data R&D Expert at Ant Financial
Personal Introduction: 2014‑2016 – Data Product Quality Lead; 2017‑2019 – External Data Integration Lead; 2019‑2022 – Data Quality Risk Architecture; 2022‑2024 – Data Security and Compliance Architecture.
Talk Title: Data Quality Governance
Outline:
1. Data Governance Overview – scope and brief introduction.
2. Data Quality Governance Challenges – causes of data quality issues, challenges faced, and governance approaches.
3. Data Quality Governance Practices – governance architecture, solution design, and real‑world case studies.
Audience Benefits:
1. Understand the challenges of financial‑grade data quality assurance.
2. Learn what “data offense and defense” entails.
3. Identify risks encountered during data R&D processes.
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DataFunTalk
Dedicated to sharing and discussing big data and AI technology applications, aiming to empower a million data scientists. Regularly hosts live tech talks and curates articles on big data, recommendation/search algorithms, advertising algorithms, NLP, intelligent risk control, autonomous driving, and machine learning/deep learning.
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