665: How to be both socially impactful and financially successful in your data career
Super Data Science: ML & AI Podcast with Jon Krohn
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Transitioning to Real-Time Data Processing and the Significance of Data Quality Monitoring
This chapter delves into the shift from offline data pipelines to real-time model serving, underscoring the crucial role of data quality and monitoring in successful machine learning operations. The speaker reflects on their professional growth from a data analyst to a software engineer, emphasizing the importance of top-notch data for insightful analysis and advocating for real-time identification of data quality problems using observability tools like Prometheus, Elasticsearch, Grafana, Jaeger, and Honeycomb.
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