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Begin by logging into your PayPal account and navigating to the 'Activity' tab. From there, select the option to download your transaction history. Choose the desired date range and select a file format that is compatible with databases, such as CSV. Export the data and save it locally on your computer.
Open the exported CSV file using a spreadsheet program (like Microsoft Excel) or a text editor. Review the data to ensure it's complete and remove any unnecessary columns or data that you do not wish to import into Starburst Galaxy. Ensure that the data is clean and formatted correctly, with consistent data types for each column.
Log into your Starburst Galaxy account. If you haven't already, set up a new cluster or connect to an existing one where you wish to import the PayPal data. Ensure that you have the necessary permissions to create tables and insert data.
Based on the CSV file structure, define the schema in Starburst Galaxy. Use the Starburst Galaxy console to create a new table with the appropriate columns and data types that match the structure of your PayPal transaction data. This can be done using SQL commands in the query editor.
With your data prepared, convert each row of the CSV file into SQL INSERT statements. This can be done using a script or manually if the dataset is small. Each statement should match the schema defined in Starburst Galaxy. Ensure that string data is enclosed in quotes and that numeric data is formatted correctly.
Access the query editor in Starburst Galaxy and paste your SQL INSERT statements. Execute these statements to upload your PayPal transaction data into the defined table. Verify that there are no syntax errors and that the data is being inserted correctly.
Once the data has been uploaded, run queries to verify that all data has been imported accurately. Check for any inconsistencies or errors in the data. It may be helpful to compare a sample of records from the original CSV file with the data in Starburst Galaxy to ensure that the transfer was successful.
By following these steps, you can manually move data from PayPal transactions to Starburst Galaxy without the need for 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.
A technology-based financial service company, PayPal facilitates online payments between customers and merchants worldwide. The PayPal platform offers secure, affordable, and convenient online financial services, making e-commerce transactions easy and secure for millions of consumers and merchants globally. Customers can link their credit or debit card or their bank account to their PayPal account to make online purchasing simpler and safer.
PayPal Transaction's API provides access to a wide range of data related to transactions processed through the PayPal platform. The following are the categories of data that can be accessed through the API:
1. Transaction details: This includes information about the transaction amount, currency, date, and time.
2. Buyer and seller information: This includes details about the buyer and seller, such as their names, email addresses, and PayPal account IDs.
3. Payment status: This includes information about the status of the payment, such as whether it has been completed, pending, or refunded.
4. Payment method: This includes information about the payment method used, such as credit card, PayPal balance, or bank transfer.
5. Shipping information: This includes details about the shipping address and shipping method used for the transaction.
6. Tax and fee information: This includes details about any taxes or fees associated with the transaction.
7. Refund and dispute information: This includes information about any refunds or disputes related to the transaction.
8. Custom fields: This includes any custom fields that were included in the transaction, such as order numbers or product descriptions.
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:
