Recently we had the 17th edition of our Data & AI Meetup. This meetup focused on Data & AI in Healthcare. Let’s have a quick recap!
16:00 – Willkommen & Intro
16:05 – BI as a Service für eine bessere Healthcare Supply Chain
Christopher Glogger, Sana Einkauf & Logistik
16:35 – AI Trends und Use cases
Andreas Kopp, Microsoft
17:20 – Visuelle Datenanalyse rund um CoViD-19
Markus Raatz, Ceteris AG
17:55 – Wrap up
Darren Cooper and I had the pleasure to welcome 200 Data & AI enthusiasts! Furthermore, we were happy to announce that our Data & AI Meetup group has 1,070 members and our brand new Data & AI LinkedIn group already has 580 members.
Reinforcement Learning of Train Dispatching at Deutsche Bahn
Dr. Tobias Keller, Data Scientist at DB Systel, showed in his session how Deutsche Bahn aims at increasing the speed of the suburban railway system in Stuttgart (S-Bahn) using Artificial Intelligence. In particular, a simulation-based reinforcement learning approach provides promising first results.
Sascha Dittmann, Cloud Solution Architect for Advanced Analytics & AI at Microsoft, showed in his presentation, how TensorFlow and other ML frameworks can be used better in a team through appropriate Microsoft Cloud services. He presented different ways of how data science experiments can be documented and shared in a team. He also covered topics such as versioning of the ML models, as well as the operationalization of the models in production.
Visual Analytics: from messy data to insightful visualization
Daniel Weikert, Expert Consultant at SIEGER Consulting, showed in his session the ease of use of Microsoft Power BI Desktop. He briefly highlighted the AI Capabilities which Power BI provides and showed a way on how to get started with messy data, doing data cleaning and visualize results in an appealing way to your audience.
Last year I started lecturing a Data Analytics course at university (as part of an MBA program). In the meanwhile, I was refining the list of books that I highly recommend to read. Three of these books form the Data Journey!
What is the Data Journey?
The Data Journey is a human-focused approach to understand the evolution of data storytelling, the power of visual analytics, and the impact of data from real-world business scenarios.
1. Info We Trust: How to Inspire the World with Data
We start our Data Journey with the book Info We Trust. This book examines all parts of the data storytelling lifecycle across disciplines. The use of marginalia and hand-drawn illustrations give you both simple lessons to take away, and insights into where to find out more. The book is full of magnificent references that inspire further reading.
Now it’s time for hands-on. Visual Analytics with Tableau covers everything you need to get started with Tableau (students get Tableau for free!). The book guides you from the first steps of connecting to data, creating different types of charts, and adding calculation fields to more advanced features such as table calculations, forecasts, and clusters, as well as R, Python, and MATLAB integration for sophisticated statistical modeling.
3. The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios
Back to business (as this course is designed for an MBA program). We close our Data Journey canon with The Big Book of Dashboards. This is a comprehensive reference book with real-world solutions for business dashboards and detailed analysis of do’s and don’ts. The examples in this book are well-organized and categorized by industry and functional business areas.
[Update 10 July 2019]: Do you need more inspiration?
#MakeoverMonday: Improving How We Visualize and Analyze Data, One Chart at a Time
Because vizzing alone is only half the fun, you should not miss the #MakeoverMonday book. Eva Murray and Andy Kriebel are icons in the data visualization community (read the interview!) and they have curated the thousands of visualizations from the #MakeoverMonday project into a practical guide that will take your design and data communication skills to the next level!
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