Presented By O’Reilly and Cloudera
Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK

Schedule: Visualization and user experience sessions

Add to your personal schedule
13:3017:00 Tuesday, 22 May 2018
Location: Capital Suite 9 Level: Non-technical
Secondary topics:  Visualization, Design, and UX
Danyel Fisher (Microsoft Research), Miriah Meyer (University of Utah)
Danyel Fisher and Miriah Meyer explore the human side of data analysis and visualization, covering operationalization, the process of reducing vague problems to specific tasks, and how to choose a visual representation that addresses those tasks. Along the way, they also discuss single views and explain how to link them into multiple views. Read more.
Add to your personal schedule
11:1511:55 Wednesday, 23 May 2018
Location: Capital Suite 14 Level: Intermediate
Secondary topics:  Visualization, Design, and UX
Jeff Fletcher (Cloudera)
As big data adoption grows, Apache Hadoop, Apache Spark, and machine learning technologies are increasingly being used to analyze ever-larger datasets, but we still have to keep telling stories about the data and making sure the message is clear. Jeff Fletcher details the tools and techniques that are relevant to data visualization practitioners working with large datasets and predictive models. Read more.
Add to your personal schedule
12:0512:45 Wednesday, 23 May 2018
Location: Capital Suite 14 Level: Non-technical
Secondary topics:  Visualization, Design, and UX
Michael Freeman (University of Washington)
Statistical and machine learning techniques are only useful when they're understood by decision makers. While implementing these techniques is easier than ever, communicating about their assumptions and mechanics is not. Michael Freeman outlines a design process for crafting visual explanations of analytical techniques and communicating them to stakeholders. Read more.
Add to your personal schedule
14:5515:35 Wednesday, 23 May 2018
Location: Capital Suite 14 Level: Beginner
Secondary topics:  Visualization, Design, and UX
Brian O'Neill (Designing for Analytics)
Do you spend a lot of time explaining your data analytics product to your customers? Is your UI/UX or navigation overly complex? Are sales suffering due to complexity, or worse, are customers not using your product? Your design may be the problem. Brian O'Neill shares a secret: you don't have to be a trained designer to recognize design and UX problems and start correcting them today. Read more.
Add to your personal schedule
16:3517:15 Wednesday, 23 May 2018
Location: Capital Suite 14 Level: Beginner
Secondary topics:  Visualization, Design, and UX
Bargava Subramanian (Independent), Amit Kapoor (narrativeVIZ Consulting)
Creating visualizations for data science requires an interactive setup that works at scale. Bargava Subramanian and Amit Kapoor explore the key architectural design considerations for such a system and discuss the four key trade-offs in this design space: rendering for data scale, computation for interaction speed, adapting to data complexity, and being responsive to data velocity. Read more.
Add to your personal schedule
16:3517:15 Thursday, 24 May 2018
Location: Capital Suite 13 Level: Intermediate
Amit Kapoor (narrativeVIZ Consulting), Bargava Subramanian (Independent)
Amit Kapoor and Bargava Subramanian lead three live demos of deep learning (DL) done in the browser—building explorable explanations to aid insight, building model inference applications, and rapid prototyping and training an ML model—using the emerging client-side JavaScript libraries for DL. Read more.