3️⃣ Data Reliability Engineering-A Three-Phase Approach to Data Quality

Anyone who has spent time working with data has seen the negative effects of data quality. Data quality incidents slow analysis to a crawl, damage executive dashboards, break user-facing applications, and impact machine learning model performance. Data quality is a big problem, and attempting to tackle it all at once can make it hard to show meaningful results.
In this presentation, Egor Gryaznov, CTO and co-founder of Bigeye, discusses a three-phase approach to addressing data quality, including how to put in place a solid toolchain and process for showing traction at each phase.
Learn more about Bigeye: www.bigeye.com/.
Get a demo: www.bigeye.com/request-demo/
#dataobservability #dataquality #datareliability #dataengineering #datareliabilityengineering

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