Understand the terms used across the platform
Entities are any moving or stationary component in your business with a location & time component. For instance: orders, riders, users, stores, and so on. Internally, they are used to define the relationships between data sources.
It is the action performed on or by the entity. For example, searches, bookings, cancellations, and so on.
Metrics let you answer the who, what, and where with respect to an entity and create clusters of areas depending on unique properties. You can create multiple types of metrics on locale.
Grid systems are essential for analysing large spatial data sets because they divide the Earth into identifiable grid cells. The data points are hexagonally bucketed on our consoles. Hence they are referred to as hexagonal heat maps.
The legend or the sliding scale is used to understand the distribution and density of any metric in the map.
The timeline is located on the bottom part of the console on Locale. It is used to slice and dice metrics across geo and time. By allowing the interaction of location with time, it enables user to get a deeper understanding of their operations by analysing the movement of the assets.
Layers are the means by which geographic datasets such as boundaries, point of interest(parking bays, restaurants, warehouse), and so on are displayed. You specify the dataset and labelling properties of a layer when you add it to a map.
You can use layers to represent specific features on the Earth’s surface. These could be,
- Points can be used to represent parking bays, restaurants, warehouses and so on.
- Polygons can be used to represent areas definition, city boundaries and so on.
Cluster by definition means number of similar things that occur together (Merriam Webster)
This feature on the Locale.ai platform allows us to keep track of areas that may exhibit common characteristics or similar patterns. We can combine different filters to identify such areas and analyse them over a certain time period.
Workflows are means by which you can automate the decisions by setting up triggers for your metrics.
For example, every time the idle time in area increases by 10%, you can automatically send incentives to the drivers to move to that area.