Enter your email business to download and customize this presentation for free
Sensor data can be represented in various ways depending on the type of data and the intended audience. Some common methods include charts, graphs, heat maps, and scatter plots. For instance, time-series data can be represented using line charts or bar graphs, while spatial data can be represented using heat maps. Scatter plots can be used to represent the relationship between two variables. In addition, advanced visualization techniques such as 3D modeling and virtual reality can also be used to represent complex sensor data.
Question was asked on:
As an example, Berinato uses Tesla Motors' Data Scientist, Anmol Garg. Garg has used visual exploration to tap into the vast amount of sensor data Tesla cars produce. He developed an interactive chart that shows the pressure in a car's tires over time. "In true exploratory form, first created the visualizations and then found a variety of uses for them: to see whether tires are properly inflated when a car leaves the factory, how often customers reinflate them, and how long customers take to respond to a low-pressure alert; to find leak rates; and to do some predictive modeling on when tires are likely to go flat. The pressure of all four tires is visualized on a scatter plot, which, however inscrutable to a general audience, is clear to its intended audience," Berinato writes.
Asked on the following presentation:
You can now save hours of work with our ultimate Charts Collection. This deck includes a variety of useful charts that you can copy and paste into any...
