Data storytelling shows up in many places and in many forms, which can confuse some people, so in this article we will help you better understand why it matters, by using the AutoPi TMU device as an example of data storytelling.
And finally, how you can create a data story to help you take data-driven decisions.
What is Data storytelling?
The ability to successfully explain insights from a dataset using narratives and visuals is known as data storytelling. It may be used to contextualize data findings and drive action.
It is practiced across many fields and is used to address a variety of challenges. For instance, storytelling through data to visualize optimization points in fleet industries.
The story is meant to explain the data and why it matters.
Data is collected and shared to help us see patterns and have insights we wouldn’t otherwise. E.g., you can look at your electric vehicle’s performance by looking at the underlying data, and then be able to determine you EV's health.
It’s important to remember, that vast amount of numbers and data alone are not meaningful to us and needs to be put into context for us to understand it. That is, because we want to make the big data meaningful to us.
Telling a story with data will help your team get from point A to point B.
Data storytelling through AutoPi
In this article, you will find out how the AutoPi IoT Platform function and how we can help you make better data-driven decisions.
The following three steps (extracting data, sorted & arranged data, and presented the data visually) are essentially analysis steps and are accomplished by the AutoPi TMU device.
The final step (data with a story) is the actual data storytelling. The technique of presenting data with a contextual narrative is known as data storytelling. There are several methods to communicate your data story. A data dashboard displays all accessible facts, allowing you to craft your story.
In following workflow, we gather as many data as requested, sort them into priority levels and apply certain criteria to differentiate for optimization.
Obs: Our Open Data Pipeline give clients full control of how and where logged data is flowing. So for this example, we will assume that the data will be sent to the AutoPi Management Cloud.
Keep reading to discover more about storytelling through AutoPi.
Step 1) Extracting data
Every time your vehicle’s engine is turned on, the Controller Area Network communication (CAN bus) system allows the Electronic Control Units (ECUs) to communicate. Depending on the type of vehicle, it can have up to 70 ECUs and each of them needs to be shared with other parts of the network.
E.g., ECUs can be battery, engine control unit, airbags, etc.
Try to look at it this way, the vehicle works as a human body and the nervous system is the CAN bus, the nervous system communicates through the human body to move arms and legs, that is the ECUs.
The communication happens instantly and generates millions and millions of data. And the AutoPi TMU device will be able to extract (log), those data in real-time.
Step 2) Sort & arrange the data
The logged data is then time stamped in real-time inside the device. However, at this point it's still just a big chunk of raw data.
Raw data is rather useless to us humans. So once the data has been logged into the device, the device will by default process the data by sorting, arranging, and filtering the data, in order to transform the raw data into actionable data insights. The sorting and arranging is based on the loggers, that has been set-up in the AutoPi cloud.
For more detailed information, you can check out our documentation site on this matter.
Step 3) Visually present the data
With a vast amount of information being collected through your vehicle, we must have a way to telling a story with data, in order to interpret it.
As the vehicle data is logged, sorted, arranged, and filtered in the device and sent to the AutoPi cloud, you are then fully capable of configuring the cloud to visualize the data through maps, graphs, tables, etc., in any way you want. By data visualization storytelling, it will give you a clear idea of what the information means by giving it visual narrative context.
Step 4) Explain the data with a story
Visual contexts are delightful to gaze at and will give you meaning to the data, however, the advantageous lies in connecting each of the visualized data in one spot, and let the data story tell you how your fleet is doing.
Through the story, you will get relevant insights into each vehicle in the fleet, and make it easier to identify trends, patterns, and outliers within large data sets.
The AutoPi Management Cloud comes with a comprehensive dashboard that displays a wide range of data. It contains everything from the number of trips each day to the amount of time and distance traveled per car, as well as fuel usage, idle time, and driving behavior.
These insights may be utilized to:
Ensure operational efficiency, with the result that your fleet is operating to its fullest potential.
Monitor the financial management and understand the total cost of ownership for each vehicle and your fleet’s overall ROI.
Employ optimal vehicle health, by incorporating data and best practices into your maintenance program.
Discover optimization possibilities, allowing you to make data-driven decisions that boost efficiency while saving money on fuel.
Interested in knowing more? Feel free to contact us on email@example.com or visit our website AutoPi.io.