In Alteryx, standard data prep is pretty simple. You load a file, clean up the text, fix the dates, and get a nice, clean table. That works great for showing what happened.
But a lot of data happens in the real world. It has a location attached to it. To really get value out of that, you need to understand where things are relative to each other.
Analysts get asked these kinds of questions all the time: "How far apart are these two things?" "Does this customer live inside our delivery zone?" "How many stores are in this specific region?"
This is where Spatial Tools come in. They let you take basic numbers and turn them into map objects that you can measure, filter, and analyse.
The Core Vocabulary: Spatial Objects
Before using the tools, it is important to understand what Alteryx is actually building. In a standard dataset, location is usually just text (an address) or numbers (latitude/longitude). Spatial tools convert these into Spatial Objects:
- Points: A specific X/Y coordinate.
- Lines: A connection between two or more points.
- Polygons: An enclosed area or shape.
The Syntax: Core Functionality
Just as the Formula tool handles string manipulation, the Spatial palette handles geometric manipulation. Here are the three fundamental tools you need to move from flat data to spatial analysis.
1. Create Points (The Creator)
Most spatial workflows start here. This tool converts numeric latitude and longitude columns into a Spatial Object. Without this step, your coordinates are just "Doubles" (numbers) that cannot be measured or mapped.
- The Function: It reads two numeric columns and generates a "Centroid" column.
- The Configuration: simply map your X Field (Longitude) and Y Field (Latitude).
- The Result: A green geometric point object is appended to your data, representing a physical location on a map grid.
2. Trade Area (The Radius)
While a "Point" represents a precise spot, a "Trade Area" represents a zone of influence. This tool takes a Spatial Point and expands it into a Polygon based on a specific radius. This is the Alteryx equivalent of a buffer in Tableau.
- The Function: It draws a circle around a point.
- The Configuration: Define the radius value (e.g., 5, 10, 20) and the unit of measurement (Miles or Kilometers).
- The Result: The specific point is transformed into a circular Polygon. This allows you to stop analysing "where is this point?" and start analysing "what falls inside this area?"
3. Spatial Match (The Connector)
This is the spatial equivalent of a Join. In a standard Join, you match data based on shared IDs (e.g., Student_ID = Student_ID). In a Spatial Match, you join data based on physical relationships (e.g., Point intersects Polygon).
- The Function: It separates records into "Matched" and "Unmatched" streams based on their geographic relationship.
- The Configuration: This tool has two inputs: Universe (U) and Target (T). You must select the spatial object from each input and define the relationship (usually "Target is Within Universe" or "Target Intersects Universe").
- The Result: The tool outputs a unified dataset where the two inputs are joined solely because they overlap in physical space.
Some Tips
1. The "Universe" vs "Target" Logic
The most confusing part of the Spatial Match tool is knowing which input goes into which anchor.
- The Issue: Mixing up the anchors can result in zero matches or errors.
- The Fix: A good rule of thumb is that the Universe (U) is the container or the larger object (like a Polygon/Area), and the Target (T) is the object you are testing (like a Point). You are checking if the Target is inside the Universe.
2. The Browse Tool is Mandatory
Unlike other visualisation tools like Tableau, Alteryx does not render maps automatically.
- The Issue: After running a spatial workflow, the results pane will simply show text.
- The Fix: Always attach a Browse Tool to the end of your spatial workflow. This is the only way to visually inspect your maps to ensure your points are landing where you expect them to.
3. Distance Tool for Precision
While Trade Area is great for filtering (determining if something is In or Out), sometimes you need a continuous measure.
- The Function: The Distance Tool calculates the precise length of the straight line between two points.
- The Output: A new numeric column containing the mileage or kilometrage, along with a cardinal direction (e.g., "SW").
Conclusion
Spatial tools like Create Points and Spatial Match give you a whole new way to ask questions of your data. Instead of just summing up columns or counting rows, you can start solving problems based on real-world location and proximity.
By utilising the three concepts covered in this blog - creating points, defining areas, and joining based on location - you can add a powerful layer of context to your analysis that standard tables just can't provide.
-- Tyler