Presented By O’Reilly and Cloudera
Make Data Work
September 11, 2018: Training & Tutorials
September 12–13, 2018: Keynotes & Sessions
New York, NY

Schedule: Visualization and user experience sessions

9:00am–12:30pm Tuesday, 09/11/2018
Making interactive browser-based visualizations easy in Python
Location: 1E 09 Level: Intermediate
James Bednar (Anaconda)
Average rating: ****.
(4.60, 5 ratings)
Python lets you solve data science problems by stitching together packages from the Python ecosystem, but it can be difficult to assemble the right tools to solve real-world problems. James Bednar walks you through using the 15+ packages covered by the new PyViz.org initiative to make it simple to build interactive plots and dashboards, even for large, streaming, and highly multidimensional data. Read more.
11:20am–12:00pm Thursday, 09/13/2018
The Vega project: Building an ecosystem of tools for interactive visualization
Location: 1A 12/14 Level: Beginner
Jeffrey Heer (Trifacta | University of Washington)
Average rating: ****.
(4.75, 4 ratings)
Jeffrey Heer offers an overview of Vega and Vega-Lite—high-level declarative languages for interactive visualization that support exploratory data analysis, communication, and the development of new visualization tools. Read more.
1:10pm–1:50pm Thursday, 09/13/2018
Augmented reality: Going beyond plots in 3D
Location: 1A 12/14 Level: Beginner
Secondary topics:  Ethics and Privacy, Financial Services, Media, Marketing, Advertising
Bob Levy (Virtual Cove, Inc.)
Average rating: ***..
(3.00, 1 rating)
Augmented reality opens a completely new lens on your data through which you see and accomplish amazing things. Bob Levy explains how to use simple Python scripts to leverage completely new plot types. You'll explore use cases revealing new insight into financial markets data as well as new ways of interacting with data that build trust in otherwise “black box” machine learning solutions. Read more.
2:00pm–2:40pm Thursday, 09/13/2018
Stories beat statistics: How to master the art and science of data storytelling
Location: 1A 12/14 Level: Non-technical
Brent Dykes (Domo)
Average rating: ****.
(4.78, 9 ratings)
Companies collect all kinds of data and use advanced tools and techniques to find insights, but they often fail in the last mile: communicating insights effectively to drive change. Brent Dykes discusses the power that stories wield over statistics and explores the art and science of data storytelling—an essential skill in today’s data economy. Read more.
3:30pm–4:10pm Thursday, 09/13/2018
Data visualization in mixed reality with Python
Location: 1A 12/14 Level: Beginner
Anna Nicanorova (Annalect)
Average rating: ***..
(3.00, 3 ratings)
Data visualization is supposed to be our map to information. However, contemporary charting techniques have a few shortcomings, including context reduction, hard numeric grasp, and perceptual dehumanization. Anna Nicanorova explains how augmented reality can solve these issues by presenting an intuitive and interactive environment for data exploration. Read more.
4:20pm–5:00pm Thursday, 09/13/2018
UX strategies for underperforming analytics services and data products
Location: 1A 12/14 Level: Non-technical
Secondary topics:  Machine Learning in the enterprise
Brian O'Neill (Designing for Analytics)
Average rating: *****
(5.00, 5 ratings)
Gartner says 85%+ of big data projects will fail, despite the fact your company may have invested millions on engineering implementation. Why are customers and employees not engaging with these products and services? Brian O'Neill explains why a "people first, technology second" mission—a design strategy, in other words—enables the best UX and business outcomes possible. Read more.