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Begin by logging into your Sendinblue account. Navigate to the Contacts section and select the list or segment you want to export. Use the export function provided by Sendinblue to download the data, typically in CSV format. Ensure you have the necessary permissions to access and export this data.
Open the exported CSV file using a spreadsheet application like Microsoft Excel or Google Sheets. Review the data to ensure it is clean and well-structured. Remove any unnecessary columns, correct any formatting issues, and ensure that the data is ready for import into Typesense. Save the cleaned data as a CSV file.
Install Typesense on your local machine. You can do this by following the instructions on the [Typesense GitHub repository](https://github.com/typesense/typesense). Ensure that you have the necessary dependencies like Ruby, Node.js, and Docker (if using Docker) installed on your system, depending on your preferred installation method.
With Typesense running locally, create a new collection to hold your Sendinblue data. Use the Typesense API to define the schema for this collection, specifying the fields that correspond to the columns in your CSV file. For example, if your CSV contains columns for "email" and "name," define these fields in the collection schema.
Write a simple script in a programming language like Python or JavaScript to convert your CSV data into JSON format. This is necessary because Typesense accepts data in JSON format. Ensure each record from the CSV is accurately transformed into a JSON object that matches the schema of your Typesense collection.
Use the Typesense API to import your JSON data into the newly created collection. This can be done through a script that reads the JSON file and sends POST requests to the Typesense server, or manually using a tool like `curl` to send the data directly. Verify that all data points have been correctly imported.
Once the data import is complete, perform a series of checks to ensure data integrity and accuracy. Use the Typesense search functionality to query the collection and verify that the data reflects what was originally in Sendinblue. Check for missing records or discrepancies, and re-import data if necessary.
By following these steps, you can successfully move your data from Sendinblue to Typesense 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.
The smartest and most intuitive platform is Sendinblue for growing businesses. Sendinblue is a comparatively easy tool to learn. Sendinblue only supports full refresh syncs meaning that each time you use the connector it will sync all available records from scratch. Sendinblue is a marketing tool that stands out from its competitors and this is also an email marketing solution for small and medium-sized businesses that want to send and automate email marketing campaigns.
Sendinblue's API provides access to a wide range of data related to email marketing and automation. The following are the categories of data that can be accessed through Sendinblue's API: 1. Contacts: This includes data related to the contacts in your Sendinblue account, such as their email addresses, names, and other contact information. 2. Campaigns: This includes data related to the email campaigns you have created in Sendinblue, such as the subject line, content, and delivery statistics. 3. Automation: This includes data related to the automated workflows you have set up in Sendinblue, such as the triggers, actions, and performance metrics. 4. Transactional emails: This includes data related to the transactional emails you have sent through Sendinblue, such as the recipient, content, and delivery status. 5. Reports: This includes data related to the performance of your email marketing efforts, such as open rates, click-through rates, and conversion rates. 6. Lists: This includes data related to the lists you have created in Sendinblue, such as the number of contacts in each list and their segmentation criteria. Overall, Sendinblue's API provides access to a comprehensive set of data that can help businesses optimize their email marketing and automation strategies.
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:
