As described in previous articles, Datacadabra works with a lot of information and data collected with the solutions. To have all these data flows useful and clear, we create overviews and diagrams so that it is clear what data comes in, how it is processed and what goes out.
An example of displaying data in an orderly fashion so that one knows what information is coming in and being processed , is a flow chart. This diagram represents, as it were, the route that data takes within a process, project or even a company. A very easy example is making a reservation in a restaurant: the customer sends his information such as date, time and company to the restaurant, which in turn processes this data by checking whether the reservation is possible. This is then fed back in the form of a confirmation or cancellation.
An advantage of organizing the flow of data is that it provides insight into multiple aspects. Because the data is structured and analyzed, the (in)efficiency of a process becomes clear and possible areas for improvement emerge. In this way, it is also possible to see more accurately and in more detail what data exists and what path this data takes, in order to allow certain aspects within a project, process or company to make more or better use of this data. This can lead to more notion and depth of related aspects to the process, in order to improve it.
Data at Datacadabra
Within Datacadabra, we make extensive use of this data. Through digital intelligence, such as computer vision and data science, we provide solutions based on this data. Take for example the MowHawk: during an existing movement, data is collected that is processed and analyzed by us. The camera on the cutterbar analyzes the roadside and detects exotics and litter and based on this the driver receives real-time mowing instructions. Because a diagram has been created regarding how the data flows in this process, one knows exactly how this data is collected, analyzed, processed and can be used. In this way, both Datacadabra and the roadside owner gain insight into the mowing process and can work toward nature-inclusive roadside management.
Thus, at Datacadabra, data is turned into actionable insights to improve the work process. So in summary, there is an existing process where data is collected or can easily be collected, then this data is analyzed and finally it provides insights that lead to improved work processes. By creating a diagram for this purpose, one knows exactly where and how the data flows and can make the best use of it.
