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

Interactive visualization for data science

Bargava Subramanian (Binaize), Amit Kapoor (narrativeVIZ)
1:30pm5:00pm Tuesday, December 5, 2017
Average rating: ***..
(3.00, 4 ratings)

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


“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.


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


Bargava Subramanian is a cofounder and deep learning engineer at Binaize in Bangalore, India. He has 15 years’ experience delivering business analytics and machine learning solutions to B2B companies. He mentors organizations in their data science journey. He holds a master’s degree from the University of Maryland, College Park. He’s an ardent NBA fan.

Photo of Amit Kapoor

Amit Kapoor


Amit Kapoor is a data storyteller at narrativeViz, where he uses storytelling and data visualization as tools for improving communication, persuasion, and leadership through workshops and trainings conducted for corporations, nonprofits, colleges, and individuals. Interested in learning and teaching the craft of telling visual stories with data, Amit also teaches storytelling with data for executive courses as a guest faculty member at IIM Bangalore and IIM Ahmedabad. Amit’s background is in strategy consulting, using data-driven stories to drive change across organizations and businesses. Previously, he gained more than 12 years of management consulting experience with A.T. Kearney in India, Booz & Company in Europe, and startups in Bangalore. Amit holds a BTech in mechanical engineering from IIT, Delhi, and a PGDM (MBA) from IIM, Ahmedabad.

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Picture of Amit Kapoor
12/07/2017 8:15am +08

Thank you all for attending the tutorial. You can find the reference material for the tutorial at The tool is available at for your use and feel free to provide us feedback on how to improve it further.