visualization

Analyzing smart cities and big data in 3D: A Geo3D journey at SmartHub

January 2, 2020

The rise of densely populated, highly built-up smart cities around the globe has stretched the capabilities of current 2D visualization techniques. With the advent of drones, IoT devices, and indoor geolocation, next-gen 3D visualizations are beginning to address this challenge. Victor Chua explores how SmartHub is gearing up for a 3D future to support cutting-edge data analytics.

Interactive visualization for data science

December 31, 2019

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. Bargava Subramanian and Amit Kapoor teach the art and science of creating interactive data visualizations.

The art of data storytelling

December 29, 2019

Isaac Reyes explores the art and science of data storytelling, covering the essential elements of a good data story, chart design and why it matters, the Gestalt principals of visual perception and how they can be used to tell better stories with data, and how to make over a poor visualization.

A unified ecosystem for market data visualization

December 16, 2019

FINRA ingests over 50 billion records of stock market trading data daily into multipetabyte databases. Janaki Parameswaran and Kishore Ramachandran explain how FINRA technology integrates data feeds from disparate systems to provide analytics and visuals for regulating equities, options, and fixed-income markets.

Bring data to life with Immersive Visualization

December 15, 2019

Data has long stopped being structured and flat, but the results of our analysis are still rendered as flat bar charts and scatter plots. We live in a 3D world, and we need to be able to enable data interaction from all perspectives. Robert Thomas offers an overview of Immersive Visualizationintegrated with notebooks and powered by Sparkwhich helps bring insights to life.

Designing a location intelligence platform for everyone by integrating data, analysis, and cartography

December 13, 2019

Geospatial analysis can provide deep insights into many datasets. Unfortunately the key tools to unlocking these insightsgeospatial statistics, machine learning, and meaningful cartographyremain inaccessible to nontechnical audiences. Stuart Lynn and Andy Eschbacher explore the design challenges in making these tools accessible and integrated in an intuitive location intelligence platform.

Fast cars, big data: How streaming data can help Formula 1

December 13, 2019

Modern cars produce data. Lots of data. And Formula 1 cars produce more than their fair share. Ted Dunning presents a demo of how data streaming can be applied to the analytics problems posed by modern motorsports. Although he won't be bringing Formula 1 cars to the talk, Ted demonstrates a physics-based simulator to analyze realistic data from simulated cars.

Five-senses data: Using your senses to improve data signal and value

December 13, 2019

Data should be something you can see, feel, hear, taste, and touch. Drawing on real-world examples, Cameron Turner, Brad Sarsfield, Hanna Kang-Brown, and Evan Macmillan cover the emerging field of sensory data visualization, including data sonification, and explain where it's headed in the future.

Model visualization

December 11, 2019

Though visualization is used in data science to understand the shape of the data, it's not widely used for statistical models, which are evaluated based on numerical summaries. Amit Kapoor explores model visualization, which aids in understanding the shape of the model, the impact of parameters and input data on the model, the fit of the model, and where it can be improved.

What ties to what? Visualizing large-scale customer text data with bipartite graphs

December 7, 2019

Which suppliers are most likely to have delivery or quality issues? Does service, product placement, or price make the biggest difference in customer sentiment? Text data from sources like email and social media can give answers. Mark Turner explains how to see the associations between any two variables in text data by combining text analytics and the bipartite graph visualization technique.

Using distributed trace data to solve performance and operational challenges

November 28, 2019

Naoman Abbas offers an overview of tools Pinterest built to process trace data and the use cases theyve enabled and shares some real-world examples. Join in to learn how to apply these techniques to your own challenges.

Prioritizing site performance improvements

November 23, 2019

Michelle Carrizosa and Iris Lieuw demonstrate how to prioritize improvements across your ecommerce site by identifying which of your pages are the most important to optimize and then looking at resource timing data to determine what affects those pages the most.

Turning high-velocity data into leverage for people

November 21, 2019

We are witnessing an explosion in the sheer mass and velocity of data. But this data is most useful if the actual builders and operatorsthe people with all the contextcan understand it and react to it quickly. Ozan Turgut discusses how to use visualization and analytics to turn data into leverage for decision making.

A few things engineers can learn from designers

October 29, 2019

Big data is great for feeding ML algorithms, but you quickly face a bandwidth issue when interfacing with humans. The brain is a fantastic information-processing machine and has an unparalleled, innate ability to detect patterns. Sbastien Pierre explains what designers can teach engineers about creating new ways to make large volumes of data understandable at the human level.

Automating decision making with big data: How to make it work

October 28, 2019

While many companies struggle to adopt big data, a number of industry leaders are leapfrogging big data adoption by going straight to automating core business processes. Andreas Schmidt presents examples from leading European companies that have overcome cultural, technical, and scientific challenges and unlocked the potential of big data in an entirely different way.

The state of visualization: Application and practice

October 20, 2019

Noah Iliinsky surveys the state of visualization, outlines the major trends in the field, and explores the directions that visualization is headed. Noah also dives into the assorted tool domainsfrom enterprise to desktop to code-basedand discusses the pros and cons and use cases of each.

Virtual reality for immersive data visualization

October 18, 2019

Ever want a superpower? Try increasing the bandwidth between your data and brain. Bob Levy explains how to pack higher dimensionality into your data exploration, enabled by virtual and augmented reality, and outlines what this means for the future of business.

Visualization is distortion: How to lie less

October 18, 2019

Seemingly harmless choices in visualization, design, and content selection can distort your data and lead to false conclusions. Aneesh Karve presents a framework for identifying and overcoming these distortions by drawing upon research in human perception, focus and context, and mobile design.

Using Julia and D3 to analyze web performance data

October 13, 2019

If you've always wanted to play around with D3 or Julia, Philip Tellis will bring you up to speed very quickly. Philip explores both Julia and D3 to demonstrate how to extract meaningful information from web-performance data and guides participants through some fun visualizations that are possible only when using these tools together.

Visualizing millions of datapoints with GPUs in the client and server

October 13, 2019

The ability to visualize millions of data points opens up a world of applications. But its hard to quickly render that much data, let alone compute anything with it. Thibaud Hottelier shares the GPU technologya hybrid client/server GPU engine using Node-OpenCL and a new library, CL.jsthat Graphistry used to break the million datapoint barrier for fast, interactive visualizations.

Measuring hard-to-measure things

October 10, 2019

GitHub has an abundance of quantitative data about what people are doing. Over the past two years, it has built a practice of qualitative research dedicated to uncovering the why. Qualitative research surfaces blind spots with product and customers and has changed the way GitHub ships features. Using three examples, Chrissie Brodigan shares how GitHub rolls features out as controlled experiments.