Machine learning in data quality management
Jennifer Yang discusses a use case that demonstrates how to use machine learning techniques in the data quality management space in the financial industry. You'll discover the results of applying various machine learning techniques in the four most commonly defined data validation categories and learn approaches to operationalize the machine learning data quality management solution.
| Talk Title | Machine learning in data quality management |
| Speakers | Jennifer Yang (Wells Fargo ECS) |
| Conference | Strata Data Conference |
| Conf Tag | Make Data Work |
| Location | New York, New York |
| Date | September 24-26, 2019 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
Traditional rule-based data quality management methodology is costly and hard to scale in the big data environment. It requires subject-matter experts within the business, data, and technology domains. A machine-learning-based data quality management methodology enables a cost-effective and scalable way to manage data quality for a large amount of data. Jennifer Yang discusses a use case that demonstrates how to use machine learning techniques in the data quality management space in the financial industry. You’ll discover the results of applying various machine learning techniques in the four most commonly defined data validation categories and learn approaches to operationalize the machine learning data quality management solution. Jennifer also shares lessons learned along the way.
