How to Use Data Prep to Accelerate Cloud Data Lake Adoption

What began as a trickle is now the mainstream: Organizations are moving to the cloud for data management. No longer is the cloud just a cheaper place to park data; it is key to supporting business-critical innovation in advanced analytics, data science, and AI as well as for end-user business intelligence, data exploration, and data visualization. Data lakes and data warehouses running on market-leading platforms such as AWS are growing fast, just as they are on the platforms of competing providers. However, as cloud-based workloads grow in number and size, organizations are facing difficult data preparation challenges. The flow of data raw, diverse, and frequently unstructured can quickly turn cloud data lakes into impenetrable swamps. Without good data preparation technologies and practices, users of all types are frustrated; their productivity and satisfaction suffer because it’s too hard to get accurate data that’s appropriately transformed and structured for their purposes.
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The Modern Toolkit for Process Excellence

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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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Modern Data Analytics in Telecom

No industry relies more on data analytics for innovation than telecommunications. From increases in data volumes, the rise of 5G, and more and more connected devices, only the organizations that invest in a modern data infrastructure will be prepared to integrate, process, and analyze the mountains of new data. What are you doing today to get ready?
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Common Mistakes to avoid when implementing your Data Governance Program

Are you planning to implement a data governance program? What are the things that practitioners often overlook or underestimate, and what are the most common mistakes they make? Join us to hear from Katherine Fraser, CEO of 1 to learn more about the key components of a successful data governance program, common mistakes made and to avoid when implementing a data governance program, and tips for maintaining a successful data governance program.
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Optimizing Your Data Analytics Resourcing

Join us for a focused discussion on Data Analytics with health system data analytics leaders. We discuss the decisions, benefits and challenges organizations face when determining how to structure and manage data assets, tools and teams. We’re excited to share diverse perspectives and answer audience questions.
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