The Modern Toolkit for Process Excellence

See in action, using a real-world use case from manufacturing, the latest toolkit for Process Excellence, powerful analytics and machine learning.How to use the Minitab toolkit to manage projects and analyse data following the Lean Six Sigma DMAIC structured approach.Discover how to power and digitalise your improvement projects and data analysis with best practice methods combined with intuitive tools.Explore how to solve problems and suggest innovations with whatever data you currently have available.Includes helpful examples of the capabilities and uses for Minitab Statistical Software, Companion by Minitab for project execution and tracking Continuous Improvement, and Salford Predictive Modeler Software for predictive analytics and machine learning.
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Spotlight

OTHER ON-DEMAND WEBINARS

Applying Data Analysis to Strategy: A Proven Approach

Learn how data professionals can refine their skills in creating and communicating practical business solutions in our recent Data Chat, “Applying Data Analysis to Strategy: A Proven Approach.” The webinar featured Barton Poulson, founder of datalab.cc, and Mike Lukianoff, a data science expert and advisor. Key topics included:
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Scaling Advanced Analytics Across Assets

This webinar presents an online introduction to scaling advanced analytics across assets, ultimately yielding faster times to diagnostic, predictive, and monitoring insights.
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Data & Analytics Leadership and Vision for 2019

Gartner

- Establish a trusted foundation of data management - Increase the data literacy of all roles in the enterprise - Scale data and analytics capabilities for the complexity of modern digital business
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Rare Disease Patient Cohort Identification Using AI/ML Models and Federated EHR-based Real-world Data Infrastructure

As rare diseases are so rare, patients are often misdiagnosed for many years, or never correctly diagnosed. Electronic health records hold much important information that can be used to correctly diagnose and treat these patients, but identification of phenotypic sets is hard to extract from reams of data.
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