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Begin by logging into your Stripe account. Once logged in, navigate to the Stripe Dashboard. This is where you can view all your transaction and customer data that you might want to export.
In the Stripe Dashboard, select the specific data you wish to export. This could be transactions, customers, invoices, etc. Go to the appropriate section (e.g., Payments) and look for an export button or link, typically found in the upper right corner of the section. Choose the CSV format for the export since it is widely compatible with Google Sheets.
After initiating the export, Stripe will generate a downloadable CSV file containing your selected data. Download this file to your computer. Ensure that you save it in a location where you can easily access it later.
Open your web browser and go to Google Sheets (sheets.google.com). If you are not already logged in, sign in using your Google account. Create a new blank spreadsheet where you will import your Stripe data.
In your open Google Sheets document, click on the "File" menu, and select "Import." In the import dialog, choose the "Upload" tab, then drag your downloaded CSV file into the window or click "Select a file from your device" to browse and select the file. Follow the prompts to import the data, ensuring you select the correct options for how the data should be imported (replace, append, etc.).
Once the data is imported into Google Sheets, you may need to format and organize it to suit your needs. Adjust column widths, format numbers, and apply filters if necessary. This will help in better analyzing and understanding the data.
Whenever you need the latest data from Stripe, repeat the export and import process. Regularly update your Google Sheet to ensure you have the most current data. Consider setting up a routine or schedule for these updates to keep your data fresh and relevant.
By following these steps, you can manually transfer data from Stripe to Google Sheets without relying on third-party connectors or integrations.
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.
Stripe is a technology company focused on helping businesses of all sizes accept web and mobile payments. Stripe software is intended to build a solid economic infrastructure for the internet at global scale. Well-known companies like Salesforce and Facebook accept online payments through Stripe software. Stripe’s innovative applications combined with their solid economic infrastructure support modern business models like crowdfunding and marketplaces. Stripe continues to innovate, partnering with tech-dominant enterprises such as Apple, Google, and Facebook to launch new capabilities.
Stripe's API provides access to a wide range of data related to payment processing and management. The following are the categories of data that can be accessed through Stripe's API:
1. Payment data: This includes information about payments made through Stripe, such as the amount, currency, and status of the payment.
2. Customer data: This includes information about customers who have made payments through Stripe, such as their name, email address, and payment history.
3. Subscription data: This includes information about subscriptions made through Stripe, such as the subscription plan, billing cycle, and status of the subscription.
4. Dispute data: This includes information about disputes raised by customers, such as the reason for the dispute and the status of the dispute resolution process.
5. Balance data: This includes information about the balance of the Stripe account, such as the available balance, pending balance, and currency.
6. Transfer data: This includes information about transfers made from the Stripe account to a bank account, such as the amount, currency, and status of the transfer.
7. Refund data: This includes information about refunds made through Stripe, such as the amount, currency, and status of the refund.
Overall, Stripe's API provides access to a comprehensive set of data related to payment processing and management, enabling businesses to effectively manage their payment operations.
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:
