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AI-driven data quality workflows deploy machine learning to automate datacleansing, detect anomalies, and validate data. Integrating AI into data workflows ensures reliable data and enables smarter business decisions. Data quality is the backbone of successful data engineering projects.
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to bring its cutting-edge automation platform that revolutionizes modern data engineering. . “This partnership is poised to tackle some of the biggest challenges faced by data executives today, including cost optimization, risk management, and accelerating the adoption of new technologies.”
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Ideally, despite the model chosen, data governance covers all strategic, tactical, and operational aspects of datamanagement, which brings us to the necessity to distinguish these and other terms. Datamanagement is the overall process of collecting, storing, organizing, maintaining, and using data.
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