What Is Spatial Analysis?Spatial analysis allows companies to analyze the locations, relationships, attributes, and proximities in geospatial data to extract insights using geographical modeling. In the past, spatial analysis was conducted solely with Geographic Information Systems (GIS) framework, which is a software framework specializing in connecting location data with descriptive information and displaying that data on a map. Today, the process leverages the capabilities of data science and machine learning, too.
Why Is Spatial Analysis Important?Spatial analysis enables companies to combine geographic and descriptive data from a variety of sources and use that data to drive geographic models and visualizations. Through data visualization, companies can see spatial data points clearly to understand where and why events happened to determine the suitability of a location for business purposes, interpret and understand change, detect patterns, and predict outcomes.
Spatial Analysis Process
Spatial analysis follows a series of well-defined steps including:
Types of Spatial Analysis
Getting Started With Spatial AnalysisTraditional spatial analysis required extensive knowledge in GIS platforms such as Esri or QGIS, but Analytic Process Automation (APA) makes it accessible to analysts and data scientists alike. The Alteryx APA Platform™ offers a unified process to transform raw data into powerful geospatial insights with:
- A wide range of geospatial data formats such as GeoJSON
- Visual, no-code tools to transform, geocode, process, and analyze spatial and hundreds of other data sources
- Tight integration of spatial reference data, including regular updates to geospatial datasets such as geocoding and drivetime analysis thanks to partnerships with TomTom, MapBox, and other vendors