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

Data visualization in mixed reality with Python

Anna Nicanorova (Annalect)
3:30pm–4:10pm Thursday, 09/13/2018
Average rating: ***..
(3.00, 3 ratings)

Who is this presentation for?

  • Data scientists, engineers, and data viz experts

Prerequisite knowledge

  • Familiarity with Python syntax

What you'll learn

  • Explore alternatives to current charts and graphs in data visualization and the code stack required to create an MR project
  • Learn how to deal with data-driven visualization in three dimensions


Data visualization is supposed to be our map to information. However, when making charts, we usually just resize lines and circles based on metrics instead of creating data-driven versions of reality. As a result, contemporary charting techniques have a few shortcomings:

  • Context reduction: In order to fit a high-dimensional dataset into a chart, you must filter, aggregate, and flatten data, which reduces the full context of information. Without context, most charts show only a part of the story, which can potentially lead to data misinterpretation or misunderstanding.
  • Numeric thinking: Humans have a hard time perceiving big numbers. While data visualization is suppose to help us conceptualize large volumes, unless the dataset is carefully prepared, 2D charts rarely give us the intuitive grasp of magnitude.
  • Perceptual dehumanization: When examining charts, it’s easy to forget that we are dealing with activity in the real world instead of lines and bars.

Anna Nicanorova explains how augmented, mixed reality (MR) can solve these issues by presenting an intuitive and interactive environment for data exploration. Three-dimensional space provides conditions to create complex data stories with more “realistic" assets, beyond lines and bars. Anna shares the architecture required to create an MR data visualization story with Python, starting with drawing 3D assets in a data-driven way and finishing with deployment on MR devices.

Photo of Anna Nicanorova

Anna Nicanorova


Anna Nicanorova is director of Annalect Labs, a space for experimentation and rapid prototyping within Annalect. During her time at Annalect, she has worked on numerous data-marketing solutions, including attribution, optimizers, quantification of content, and image recognition technology. She was part of Annalect team that won the 2015 I-Com Data Science Hackathon. Anna is cofounder of the Books+Whiskey meetup and a coding volunteer teacher with ScriptEd. She holds an MBA from the Wharton School at the University of Pennsylvania and a BA from Hogeschool van Utrecht.