Analytics Toolbox for BigQuery
Examples
In this section we provide a set of examples that showcase how to leverage the functions of our Analytics Toolbox to unlock advanced spatial analyses in your data warehouse platform. They cover a broad range of use cases with methods for data transformations, enrichment, spatial indexing in Quadkey and H3, statistics, clustering, spatial data science methods and more.
The Analytics Toolbox can be leveraged from the SQL Query editor in Builder, your data warehouse console, or in SQL and Python Notebooks using the SQL clients provided by the different cloud platforms.
Cannibalization is a very common analysis in retail that consists in quantifying the impact of new store openings on existing stores.
The Twin Areas analysis can be used to build a similarity score with respect to an existing site (e.g. the location of your top performing store) for a set of target locations, which can prove an essential tool for Site Planners looking at opening, relocating, or consolidating their retail network. In this example we select as potential origin locations the locations of the top 10 performing liquor stores in 2019 in Iowa, US from the publicly available [Liquor sales dataset](https://data.iowa.gov/Sales-Distribution/Iowa-Liquor-Sales/m3tr-qhgy) to find the most similar locations in Texas, US.
We find the best new location for a specific target demographics using spatial indexes and advanced statistical functions.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 960401.