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Teams need to trust the predictions created by analytic solutions. Yet measuring, monitoring and improving the underlying data quality is often overlooked.
This course teaches the foundational data stewardship, quality and governance capabilities needed to enable mass adoption of data, analytics, and AI throughout the organization. Students learn how to build in context, structure, and quality from data capture through curation.
Define, measure and improve data quality for analytics solutions.
Monitor quality thresholds, calculations and automations to continually improve performance.
Build a shared accountability across teams to support and scale capabilities.
Learn the importance and methods for Data Stewardship, Quality, and Governance as levers for scaled analytics, AI, and Data Enablement.
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Apply widespread Data Stewardship tactics to accelerate analytics transformation. Develop common tools and spaces for your teams to curate and share trustworthy data sets.
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Define, measure, and improve the quality of a data set. Map the process, roles and responsibilities to deploy an analytic solution as well as potential failure modes to measure & monitor for.
Define, measure and improve data quality for analytics solutions.
Monitor quality thresholds, calculations and automations to continually improve performance.
Build a shared accountability across teams to support and scale capabilities.
This enables our tailored training experience. We want to make sure each class is right for you, and that you will get the most value out of completing it.
We've created a simple form below to help you get the process started...
I felt like we hit our stride and were sharing organizational context and prior experiences alongside course concepts in a way that elevated the training. I really enjoyed our discussions.
