Images courtesy of xyzt.ai using Otonomo data Free GIS and Data Visualization Tools Here are examples of Otonomo vehicle data visualized by xyzt.ai: Traffic analyst teams can also easily share insights with other users and create multiple projects for easy collaboration. xyzt.ai allows analysts to view several attributes and combinations of attributes for a truly holistic and layered traffic analysis. The location data analysis platform highlights the power of Otonomo’s rich datasets. They offer traffic analysts options to choose from a diverse set of analytics tools and alerts to focus on wait time analysis, state of change, direction, density analysis, and more. xyzti.ai allows users to define areas and time slots to monitor and analyze location data. Xyzt.ai, Otonomo’s visualization partner, is a cloud based SaaS platform specializing in innovative visual analytics of big location and traffic data. Image courtesy of xyzt.ai using Otonomo data Otonomo Data Analysts’ Picks for the Best Data Visualization and GIS Tools for Traffic Data Analysis Once the data is laid out, it’s easy to see overall and specific trends, spot weak points, and identify hidden opportunities. Heatmaps are pretty straightforward and the intensity of the color (from cool to warm) represents the value progression. Image generated by Tableau using Otonomo data Heatmaps are Essential for Quick Analysis For example, the number of trips during a specified time frame among several cities. Image generated by Python Pandas using Otonomo data Bar Charts Easily Highlight Comparisonsīar charts are quite effective for comparing the quantities of different categories/attributes along a specific time frame. Examples of this include examining speed values per hour of the day or vehicle volumes over time in specific locations. There are many different ways to analyze vehicle data on a histogram, most commonly, specific attributes are examined over multiple time frames. They represent the dynamics of one variable over a specific period of time, and are used to understand how the data is going to change with different filters. Image from the Otonomo Vehicle Data Platform Histograms are Key for Showcasing Different Dynamics Over Time You can also use tools with a similar feature that allows you to zoom in when looking at datasets comprising a larger area. Otonomo’s platform has a user-friendly UI to draw a polygon on maps to easily generate reports. This is really useful if you want to focus on a specific area. Drawing a custom polygon on a map can provide data within specific coordinates. While selecting areas to analyze, like a city, sometimes issues result, such as excluding highways or relevant suburbs. One of the cool features Otonomo has is allowing its users to extract data using a geofencing polygon, which requires no code. Geofencing Polygons Zoom in on What’s Important These tips will help you know what to look for when choosing data visualization tools. Traffic analysts can get the most out of connected vehicle data and their GIS tools by following a few pro tips for assessing data. 4 Capabilities to Look for in a Data Visualization Tool They offered some key capabilities to keep in mind when choosing data analysis tools and presented some of their favorite tools – both free and paid. We asked our data analysts to share some of their favorite traffic mapping software. Otonomo data integrates easily with any mapping or BI tool you can think of, due to its easy API and CSV exports. In order to extract the most valuable insights from such nuanced data, traffic data analysts need to choose the right data visualization and GIS tools for their traffic analysis. The unique richness of Otonomo data is suited for insights to help improve smart cities, traffic management, road safety, and countless other use cases that begin with solid traffic data analysis. Otonomo’s connected vehicle data is particularly rich due to its diverse data attributes that provide many parameters: location, speed, engine status, road sign data, hazard data, and more. So big, in fact, that many app developers and data analysts find that data visualization is the best way to make sense of connected car and traffic data. Connected vehicle data is powerful, and it is big.
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