TensorFlow Data Validation: Data Analysis and Validation in Continuous ML Pipelines
Summary: TFDV offers scalable data analysis and validation for continuous ML pipelines, elevating data quality as a first-class concern. Integrated with TensorFlow Extended (TFX), it provides production-grade data monitoring, schema validation, and anomaly detection; open-sourced and widely adopted. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Emily Caveness
- 2. Paul Suganthan G. C.
- 3. Zhuo Peng
- 4. Neoklis Polyzotis
- 5. Sudip Roy
- 6. Martin Zinkevich
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,096 | Saga: A Scalable Framework for Optimizing Data Cleaning Pipelines for Machine Learning Applications | 2023 | SIGMOD | 4.583522e-05 |
| 8,917 | DQDF: Data-Quality-Aware Dataframes | 2022 | VLDB | 4.4229886e-05 |
| 10,777 | Unlocking the Power of CI/CD for Data Pipelines in Distributed Data Warehouses | 2025 | VLDB | 4.1905499e-05 |
| 10,871 | T-Assess: An Efficient Data Quality Assessment System Tailored for Trajectory Data | 2025 | VLDB | 4.1905499e-05 |
| 11,282 | CM-Explorer: Dissecting Data Ingestion Problems | 2023 | VLDB | 4.1905499e-05 |
| 11,344 | FILA: Online Auditing of Machine Learning Model Accuracy under Finite Labelling Budget | 2022 | SIGMOD | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,481 | Automating Large-Scale Data Quality Verification | 2018 | VLDB | 0.00011715754 |
| 1,629 | Data Cleaning: Overview and Emerging Challenges | 2016 | SIGMOD | 0.00011073148 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,006 | Data Platform for Machine Learning | 2019 | SIGMOD | 6.5371762e-05 |
| 11,319 | Data Management Opportunities for Foundation Models | 2022 | CIDR | 4.1905499e-05 |
| 7,138 | Ease.ml/ci and Ease.ml/meter in Action: Towards Data Management for Statistical Generalization | 2019 | VLDB | 4.8164681e-05 |
| 1,422 | Data Management Challenges in Production Machine Learning | 2017 | SIGMOD | 0.00012050431 |
| 7,840 | Auto-Validate: Unsupervised Data Validation Using Data-Domain Patterns Inferred from Data Lakes | 2021 | SIGMOD | 4.6337164e-05 |
| 9,116 | Towards Observability for Production Machine Learning Pipelines | 2022 | VLDB | 4.3886184e-05 |
| 2,456 | Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities | 2021 | SIGMOD | 8.7649259e-05 |
| 6,526 | Data Collection and Quality Challenges for Deep Learning | 2020 | VLDB | 5.0219175e-05 |
| 1,481 | Automating Large-Scale Data Quality Verification | 2018 | VLDB | 0.00011715754 |
| 2,175 | tf.data: A Machine Learning Data Processing Framework | 2021 | VLDB | 9.3745231e-05 |