22-25 April 2026 
A practical guide to using charts & graphs!
2015TL; DR
Within Azure we have a rich ecosystem of AI services that can be leveraged to gain new insights into your data. This session will give you an easy to digest breakdown of the key services that matter and how to approach each one; Cognitive Services, Bot Framework, Azure Machine Learning Studio, Databricks, Notebooks, the Azure ML SDK for Python and the Azure ML Service
Session Details
There are many books and articles on how to design a dashboard or create a pretty chart. But how do you know which graphical representation is the right one for your data? What kind of chart will answer the right business question? Should you use a line, bar, or pie chart? (Yes, even a pie chart. Stephen Few is not always correct in a business context.) When should you use multiple series on a chart versus using small multiples? What is the best way to show contribution to the whole? Why would you mix a line and bar chart?
The session will answer these and other questions by taking a practical approach, not a theoretical one. Discover how to give your users and management what they are looking for in a way that balances information content vs. visual impact. See visualizations that not only answer business questions, but draw the eye to the most important aspects of the data.
Learn the difference between visual discovery, infographics, and what most of us actually do – using charts and graphs for reporting purposes. Creating a repeatable process is different than an individual user searching for insights in a data set or an infographic that is making a point about a fixed data set. Discover how to design a chart that works day after day, month after month, regardless of which product or region users want to slice.
A dashboard is more than just a report with 4 charts. Learn what makes a dashboard a unique reporting vehicle. Find out not only how to make a good chart, but how to combine charts into an effective dashboard. Determining where a chart is placed on a dashboard is important as different areas have varying visual impact. Discover when a table is more appropriate than a graph and how to design the table for maximum effect.
The session will take a case study approach. We’ll study different data sets to highlight how different charts bring out different aspects of the data. Maybe more importantly, we’ll take a look at which charts don’t really show anything interesting at all and then transform them into effective charts