Great Expectations
PulseAugur coverage of Great Expectations — every cluster mentioning Great Expectations across labs, papers, and developer communities, ranked by signal.
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TDDA Book Chapter 7 on Data Validation Released, tdda Library v3.2 Adds Polars Support
The TDDA Book's Chapter 7, focusing on practical constraints in data validation, is now available online. This chapter concludes the data validation section, discussing non-tabular data, spreadsheets, measurement regula…
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LLM data pipeline integration faces hidden data quality and security risks
Integrating Large Language Models (LLMs) into data pipelines presents significant challenges beyond just selecting the right model. A key issue is that LLMs do not fail loudly like traditional data systems; instead, the…
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MLOps Guides Detail Frameworks, Workflows, and Real-Time AI Deployment
This cluster of articles focuses on Machine Learning Operations (MLOps), detailing the complete frameworks and workflows necessary for managing the machine learning lifecycle. The pieces cover building continuous delive…
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Eugene Yan details robust testing strategies for data and ML pipelines
Eugene Yan's article explores methods for creating more resilient tests for data and machine learning pipelines. The author discusses why existing tests often fail even when new code is correct, attributing this to the …