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Begin by logging into your Strava account on a web browser. Navigate to your profile settings by clicking on your profile picture in the top-right corner, then select "Settings." From the left sidebar, choose "My Account" and click on "Download or Delete Your Account." Here, you will find the option to request an export of your data. Strava will compile your data and email you a link to download it as a ZIP file.
Once you receive the email from Strava with your data export link, click the link to download the ZIP file to your computer. Use a file extraction tool (such as the built-in extractor on Windows or macOS) to extract the contents of the ZIP file to a folder on your computer. Inside, you'll find several files, including those with activity data in CSV format.
Locate the CSV files within the extracted folder. These files contain your activity data and are typically named with the activity type, such as "activities.csv." Double-click on the CSV file you wish to import into Google Sheets to open it in a spreadsheet application like Microsoft Excel or any text editor that supports CSV format. Review the data to ensure everything is intact and correct.
Open Google Sheets in your web browser by navigating to https://sheets.google.com. Click on the "+" button to create a new, blank spreadsheet. This new sheet will be used to import and store your Strava data.
In the new Google Sheet, click on "File" in the top menu, then select "Import." Choose "Upload" and then drag your CSV file into the window or click "Select a file from your device" to browse for the file. Once uploaded, choose "Replace spreadsheet" to import your data into the new Google Sheet. This will populate the sheet with the data from your CSV file.
After the import is complete, review the data in Google Sheets to ensure it appears correctly. You may need to adjust column widths, change date formats, or perform other formatting tasks to make the data more readable. Use Google Sheets features to sort, filter, or analyze your data as needed.
For future data updates, repeat the export process from Strava and use Google Sheets' "Import" function to bring in new data. To streamline this process, consider using Google Sheets' "Import Data" feature or writing a script in Google Apps Script to automate data imports. However, this would require some programming knowledge and is optional if manual updates suffice.
FAQs
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
Strava is a late-stage venture company and fitness-focused social app for tracking exercise. It is one of the most popular fitness apps for those with a competitive edge. Strava is an online network where runners and cyclists can record their activities, compare performance, and compete with their community. Strava is a worldwide community of millions of runners, cyclists and triathletes, united by the fellowship of sport. Strava is a free digital service available through both mobile applications and the web.
Strava's API provides access to a wide range of data related to user activities on the platform. The following are the categories of data that can be accessed through Strava's API:
1. Athlete data: This includes information about the user's profile, such as name, age, gender, weight, and location.
2. Activity data: This includes information about the user's activities, such as distance, duration, speed, elevation, and heart rate.
3. Segment data: This includes information about the user's performance on specific segments, such as the segment name, distance, elevation, and leaderboard rankings.
4. Route data: This includes information about the user's created routes, such as the route name, distance, elevation, and map coordinates.
5. Club data: This includes information about the user's clubs, such as the club name, description, and member list.
6. Gear data: This includes information about the user's gear, such as the gear name, type, and usage statistics.
7. Authorization data: This includes information about the user's authorization status, such as access tokens and refresh tokens.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
