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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.
PrestaShop is an open-source e-commerce platform whose cutting-edge technology powers over 300,000 e-commerce businesses globally. The PrestaShop mission is to allow the open-source community to “put their heads together” to develop superior eCommerce software—which they achieved in 2016, winning CMS Critic Award for Best eCommerce Software. The perfect solution for creating and growing an online business, PrestaShop provides all the features needed to achieve success.
PrestaShop's API provides access to a wide range of data related to e-commerce stores. The following are the categories of data that can be accessed through PrestaShop's API:
1. Products: Information related to products such as name, description, price, stock, images, and categories.
2. Customers: Data related to customers such as name, email, address, and order history.
3. Orders: Information related to orders such as order number, customer details, products ordered, and payment information.
4. Categories: Data related to product categories such as name, description, and parent categories.
5. Manufacturers: Information related to manufacturers such as name, description, and logo.
6. Suppliers: Data related to suppliers such as name, address, and contact information.
7. Carriers: Information related to shipping carriers such as name, description, and shipping rates.
8. Employees: Data related to employees such as name, email, and access permissions.
9. Languages: Information related to languages used in the store such as name, code, and translations.
10. Currencies: Data related to currencies used in the store such as name, code, and exchange rates.
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.
PrestaShop is an open-source e-commerce platform whose cutting-edge technology powers over 300,000 e-commerce businesses globally. The PrestaShop mission is to allow the open-source community to “put their heads together” to develop superior eCommerce software—which they achieved in 2016, winning CMS Critic Award for Best eCommerce Software. The perfect solution for creating and growing an online business, PrestaShop provides all the features needed to achieve success.
BigQuery is an enterprise data warehouse that draws on the processing power of Google Cloud Storage to enable fast processing of SQL queries through massive datasets. BigQuery helps businesses select the most appropriate software provider to assemble their data, based on the platforms the business uses. Once a business’ data is acculumated, it is moved into BigQuery. The company controls access to the data, but BigQuery stores and processes it for greater speed and convenience.
1. First, you need to obtain the necessary credentials to connect your PrestaShop source connector. This includes your PrestaShop URL, API key, and API secret key. You can find these credentials in your PrestaShop account under the "Advanced Parameters" tab.
2. Once you have your credentials, open the Airbyte dashboard and click on "Sources" in the left-hand menu.
3. Click on the "Create a new connection" button and select "PrestaShop" from the list of available connectors.
4. In the "Connection Configuration" page, enter your PrestaShop URL, API key, and API secret key in the appropriate fields.
5. Click on the "Test" button to ensure that your credentials are correct and that Airbyte can connect to your PrestaShop account.
6. If the test is successful, click on the "Save & Continue" button to proceed to the next step.
7. In the "Schema Selection" page, select the tables that you want to replicate from your PrestaShop account.
8. Click on the "Save & Continue" button to proceed to the final step.
9. In the "Sync Configuration" page, configure the replication settings for your PrestaShop data. This includes the frequency of data replication, the destination for your data, and any transformations that you want to apply to your data.
10. Click on the "Save & Test" button to finalize your PrestaShop source connector configuration. Your data will now be replicated from your PrestaShop account to your destination according to your configured settings.
1. First, navigate to the Airbyte dashboard and select the "Destinations" tab on the left-hand side of the screen.
2. Scroll down until you find the "BigQuery" destination connector and click on it.
3. Click the "Create Destination" button to begin setting up your BigQuery destination.
4. Enter your Google Cloud Platform project ID and service account credentials in the appropriate fields.
5. Next, select the dataset you want to use for your destination and enter the table prefix you want to use.
6. Choose the schema mapping for your data, which will determine how your data is organized in BigQuery.
7. Finally, review your settings and click the "Create Destination" button to complete the setup process.
8. Once your destination is created, you can begin configuring your source connectors to start syncing data to BigQuery.
9. To do this, navigate to the "Sources" tab on the left-hand side of the screen and select the source connector you want to use.
10. Follow the prompts to enter your source credentials and configure your sync settings.
11. When you reach the "Destination" step, select your BigQuery destination from the dropdown menu and choose the dataset and table prefix you want to use.
12. Review your settings and click the "Create Connection" button to start syncing data from your source to your BigQuery destination.
With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.
We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
Ready to get started?
Frequently Asked Questions
PrestaShop's API provides access to a wide range of data related to e-commerce stores. The following are the categories of data that can be accessed through PrestaShop's API:
1. Products: Information related to products such as name, description, price, stock, images, and categories.
2. Customers: Data related to customers such as name, email, address, and order history.
3. Orders: Information related to orders such as order number, customer details, products ordered, and payment information.
4. Categories: Data related to product categories such as name, description, and parent categories.
5. Manufacturers: Information related to manufacturers such as name, description, and logo.
6. Suppliers: Data related to suppliers such as name, address, and contact information.
7. Carriers: Information related to shipping carriers such as name, description, and shipping rates.
8. Employees: Data related to employees such as name, email, and access permissions.
9. Languages: Information related to languages used in the store such as name, code, and translations.
10. Currencies: Data related to currencies used in the store such as name, code, and exchange rates.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey: