Power BI Integration with Azure Machine Learning Chad

Power BI Integration with Azure Machine Learning Chad Dotzenrod Analytics & Cloud Evangelist at SWC Technology Partners

Meet Your Presenter: Chad Dotzenrod • Analytics & Cloud Evangelist at SWC Technology Partners • PUG Membership: Greater Chicago Power BI User Group • 20 Years of work in Data and Analytics • Education: NDSU & De. Vry Keller • Fun facts! Avid fisherman and competitive BBQ contestant • Follow me on Twitter: @cdotzenrod • Connect with me on Linked. In: chaddotzenrod • Email: cjd@swc. com

Agenda • Quick Audience Survey • Why Is This Important? • Integration Scenarios • Review Azure Machine Learning Workbench • Demo • Q&A

• Making Decisions with Data • Descriptive > Predictive > Prescriptive • Command Control via Power BI • Trust but Verify • Understanding what the algorithms, models, and machines are doing to us! • Use Power BI to question everything happening with the data • Prove the ROI • Show and Tell a story that is impactful to the organization • Steer clear of Data Science jargon when presenting to citizens!

• Microsoft TDSP Process • Data Science is a process! • No Shortcuts!

Who is Solving What? Use Case Automotive Manufacturing Consumer Real-time Optimization Strategic Optimization Predictive Analytics Predictive Maintenance Radical Personalization Trend/Anomaly Discovery Forecasting Source: Mc. Kinsey – The Age of Analytics Report, Dec 2016 Finserve Energy Pharma Public Media Logistics

Integration Scenarios Plentiful Options • Batch • Real-Time • On-Demand Complexity & Skillsets • Latency/Data Prep/Cost • SQL/R/Python/Azure

Azure Machine Learning Studio Citizen Data Science Tool Visual Editor Reasonable Cost Gallery Support Pure Paa. S

Azure Machine Learning Studio Details What skillset is needed to get started? How much does it cost? Deployment Options Integration with Excel, LOB Apps, and Power BI is useful in telling the model story

Azure Machine Learning Workbench Professional Data Science Tool Enhanced Data Preparation Model Management Model Experimentation Bridges On-Premise, Hybrid, & Cloud

AML Workbench Details Deployment Targets: How is this different from AML Paa. S? How much does it cost? • Docker Containers (Local or Azure) • Virtual Machines (Azure) • SQL Server Machine Learning Server (Local or Azure)* • Azure Io. T Edge* Integration with Visual Studio AI Tools *These deployment targets are not currently in preview yet but are on the roadmap Excellent Companion Tool for Power BI Solution Builders!

Power BI Challenges for AML Workbench • • • Data Profiling is not easy enough and many don’t know how to approach Working with “Big Data” can be cumbersome and slow Cleansing capabilities are excellent but not as rich as AMLW. No seamless Integration with GIT or other code repositories Power BI Adoption Speedbumps: • Hard data challenges (complicated transforms) might have to go to the ETL Team • Performance data challenges might go to Database Team (EDW, Cubes, In-memory) • Functional challenges – I can’t do X with PBD and I don’t know how to write R Scripts

Thank You for Attending! Don’t forget to join your local PUG to enjoy year-round networking and learning. www. pbiusergroup. com/chicagoland www. pbiusergroup. com/milwaukee Twitter: @cdotzenrod Linked. In: chaddotzenrod Email: cjd@swc. com