Presented By O'Reilly and Cloudera
Make Data Work
Dec 4–5, 2017: Training
Dec 5–7, 2017: Tutorials & Conference
Singapore

Interactive visualization for data science

Bargava Subramanian (Independent), Amit Kapoor (narrativeVIZ Consulting)
1:30pm5:00pm Tuesday, December 5, 2017
Design, UX, visualization, and VR, Machine Learning
Location: 310/311 Level: Beginner

Who is this presentation for?

  • Data scientists and analysts and BI developers

Prerequisite knowledge

  • A basic understanding of Markdown
  • Familiarity with data visualization (useful but not required)

Materials or downloads needed in advance

  • A laptop with a modern browser installed (All materials and instructions will be posted to the course GitHub repository.)

What you'll learn

  • Learn the principles of interactive data visualization, including grammar, types, color, annotation, flow, animation, and interaction
  • Understand different approaches for creating data visualizations, such as static graphics, web-based interactive graphics, and interactive data products
  • Explore visualization in different statistical contexts, including exploration, modeling, and communication, to gain insight from data

Description

“A picture is worth a thousand words. An interface is worth a thousand pictures.”—Ben Shneiderman

Ever-increasing computational capacity has enabled us to acquire, process, and analyze larger and larger datasets and information. However, the human memory and attention required to use this data is limited and has remained relatively constant. Data visualization can enable us to compress data and encode it in ways that aid perceptual, cognitive, and emotional capacity required to comprehend, retain, and make decisions using this data.

One of the challenges in traditional data visualization is that they are static and have bounds on limited physical/pixel space. Interactive visualizations allows us to move beyond this limitation by adding layers of interactions. We’ve all seen wonderful interactive data visualizations on the web, such as those from the New York Times’s Upshot or FiveThirtyEight, and may want to bring similar interaction principles to our business dashboards. But crafting an interactive data visualization on the web is hard, especially if you have limited web programming background. More often than not, data scientists want to demonstrate or showcase their work as a dashboard and are required to get approval from stakeholders before the dashboard is moved to production by frontend engineers.

Bargava Subramanian and Amit Kapoor teach the art and science of creating interactive data visualizations, providing hands-on experience with using simple tools in the browser, including visdown and polestar, to conduct exploratory data analysis for large datasets and visually communicate insights from data.

Outline

Grammar of interactive graphics: The four layers of abstraction

  • Data layer: Data types and transformations
  • Visual layer: Variable mapping, marks, channels, scales, coordinate system, and layouts
  • Annotation layer: Titles, axes, legends, grids, references, and text
  • Interaction layer: Navigation, transition, selection, highlighting, filtering, brushing and linking, sorting, and animation

Tools landscape

Creating a static visualization

  • Visualizing a multidimensional dataset
  • Playing with marks, channels, color, scales, and coordinates
  • Adding labeling and annotation

Adding an interaction layer

  • Adding interactive data-model manipulation
  • Exploring common interaction patterns: Select, explore, reconfigure, encode, filter, and drill-down

Creating an interactive data visualization

  • Building a full interactive data dashboard

Additional pointers, wrap-up, and Q&A

  • Additional concepts in interaction: Scrolling, animation, and story points
  • Q&A
Photo of Bargava Subramanian

Bargava Subramanian

Independent

Bargava Subramanian is a machine learning engineer based in Bangalore, India. Bargava has 14 years’ experience delivering business analytics solutions to investment banks, entertainment studios, and high-tech companies. He has given talks and conducted numerous workshops on data science, machine learning, deep learning, and optimization in Python and R around the world. He mentors early-stage startups in their data science journey. Bargava holds a master’s degree in statistics from the University of Maryland at College Park. He is an ardent NBA fan.

Photo of Amit Kapoor

Amit Kapoor

narrativeVIZ Consulting

Amit Kapoor is interested in learning and teaching the craft of telling visual stories with data. At narrativeVIZ Consulting, Amit uses storytelling and data visualization as tools for improving communication, persuasion, and leadership through workshops and trainings conducted for corporations, nonprofits, colleges, and individuals. Amit also teaches storytelling with data as guest faculty in executive courses at IIM Bangalore and IIM Ahmedabad. Amit’s background is in strategy consulting, using data-driven stories to drive change across organizations and businesses. He has more than 12 years of management consulting experience with AT Kearney in India, Booz & Company in Europe, and more recently for startups in Bangalore. Amit holds a BTech in mechanical engineering from IIT, Delhi, and a PGDM (MBA) from IIM, Ahmedabad. Find more about him at Amitkaps.com.

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