Extracting Data from Map APIs into Google Sheets & Looker Studio

Extracting Data from Map APIs into Google Sheets & Looker Studio This report answers whether data from map APIs, primarily focusing on the Google Maps Platform, can be extracted directly into Google Sheets or Looker Studio for analysis and visualization. Executive Summary There is no direct, one-click integration to pull data from Google Maps APIs into Google Sheets or Looker Studio. However, extraction is entirely possible and commonly done through indirect methods that require some technical setup. For Google Sheets: The most effective method is using Google Apps Script to call the API and write the data directly into a sheet. This is ideal for smaller, on-demand data pulls. For Looker Studio: The best practice is to first load the API data into an intermediate data source that Looker Studio can connect to, such as Google Sheets (for simple cases) or BigQuery (for larger, more automated workflows). Method 1: Extraction into Google Sheets The most direct way to get Google Maps API data into Google Sheets is by using its built-in scripting environment. Tool: Google Apps Script Process Overview: Get a Google Maps API Key: You must have a valid API key from the Google Cloud Platform, with the necessary APIs (e.g., Geocoding API, Places API) enabled and a billing account attached. Open Apps Script: From your Google Sheet, go to Extensions > Apps Script. Write the Script: A script is written to perform three main functions: Fetch Data: Use the UrlFetchApp service to make a call to the specific Google Maps API endpoint (e.g., the Geocoding API to get coordinates for a list of addresses). The API key and query parameters are included in the request URL. Parse Data: The API returns data in JSON format. The script uses JSON.parse() to convert this text into a workable JavaScript object. Write to Sheet: The script extracts the desired information (like latitude, longitude, place ID, etc.) from the parsed object and writes it into the appropriate cells in your sheet using the getRange().setValues() method. Run the Script: The script can be run manually from the editor or triggered automatically by a custom menu item, a button in the sheet, or on a time-based schedule. Best For: Enriching existing data (e.g., getting coordinates for a list of addresses). Small to medium-sized datasets. On-demand or infrequent data pulls. Method 2: Extraction for Looker Studio Looker Studio works by connecting to existing data sources. Since an API is not a persistent data source, you must first store its output somewhere. Sub-Method A: Using Google Sheets as an Intermediary This is the simplest approach for Looker Studio. Process Overview: Follow the process described in Method 1 to pull the Google Maps API data into a Google Sheet. In Looker Studio, create a new data source and select the Google Sheets connector. Connect to the sheet containing your extracted map data. You can now build charts and reports in Looker Studio based on this data. Best For: Users who are comfortable with Apps Script. Projects where the data does not need to be updated in real-time. Visualizing smaller datasets. Sub-Method B: Using BigQuery as an Intermediary (Recommended for Scale) This is the most robust and scalable method for handling large amounts of data or for automating the entire workflow. Process Overview: Automated Fetching: Set up a cloud-based, serverless function (e.g., Google Cloud Function) that runs on a schedule. API Call: This function contains code (e.g., in Python or Node.js) that calls the Google Maps API to fetch the required data. Load to BigQuery: The function processes the JSON response and loads the data into a table in BigQuery, Google's data warehouse. Connect Looker Studio: In Looker Studio, create a new data source using the native BigQuery connector and point it to the table containing your map data. Best For: Large or frequently updated datasets. Fully automated, scheduled data extraction. Enterprise-level projects requiring a scalable and reliable data pipeline. Key Considerations & Requirements Before starting, be aware of the following: API Keys & Billing: A Google Cloud Platform project with an active billing account is required to use the Google Maps Platform APIs. Monitor your usage closely, as API calls incur costs. Google Maps Platform Terms of Service: Google has specific restrictions on how you can use and store its data. You generally cannot store Google's data indefinitely. Caching is permitted for short periods to improve performance, but creating a permanent, large-scale copy of Google's location database is prohibited. Always review the current ToS before storing data. Technical Skill: Apps Script: Requires basic JavaScript knowledge. BigQuery Pipeline: Requires intermediate knowledge of a programming language (like Python) and familiarity with cloud services (Cloud Functions, BigQuery).