Database Strategies for Modern BI and Analytics

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.

Data scientists’ time is valuable. Computing resources are expensive. With only 87% of projects ever making it to production (Source: VentureBeat), organizations often overcommit to costly projects that bear little fruit. Data science teams need a way to assess project feasibility without diving head first.

To compete in today’s digital economy, enterprises require new ways to expand AI across their entire organization. Nearly all firms want to do more with data science, but they don’t know where to begin or how to properly empower citizen data scientists to avoid common AI gone wrong accidents. In this session, we will discuss how to approach your journey into citizen data science with existing analytics talent. Proven best practices and lessons learned from successful early adopters of augmented data science will be shared. We will walk through example initiative roadmaps, recommended staffing, upskilling, mentoring and ongoing governance.

As organizations move into the cloud, the choices for handling high-scale data for analytical use are flourishing and evolving. How do we address BI/analytics, data science, security/application monitoring, and log data management workloads? Do we really need potentially overlapping warehouse, data lake, and security and observability capabilities on top of object storage, or can an evolved data lake or emerging “lakehouse” platform do it all? Join Doug Henschen, VP and principal analyst at Constellation Research and Thomas Hazel, Chief Technology and Science Officer at ChaosSearch for a broad-ranging discussion on the challenges and strategy considerations that go into choosing the right platform.