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Begin by logging into your Mailjet account. Navigate to the SMS section and locate the option to export your SMS data. You may need to filter the data you require and then select the export option, typically available in CSV or Excel format. Save this file to your local machine.
Open the exported file in a spreadsheet application like Excel or Google Sheets. Review the data to ensure it is clean and organized. Remove any unnecessary columns or rows and format the data according to Convex's import requirements. This may include renaming headers or converting data types.
Log into your Convex account and navigate to the database section where you wish to import the SMS data. Ensure you have the necessary permissions to add or modify data within this database.
Before importing, you need to ensure that the Convex database has a schema or table structure that matches the data you're importing. Create a new table or adjust an existing one by adding fields that correspond to the columns in your prepared data file.
Convex provides a Command Line Interface (CLI) for database operations. Use the Convex CLI to import your data file directly into the Convex database. You may need to write a script or use a command that reads the CSV file and inserts the data into the appropriate fields in the Convex table.
After importing, review the data within Convex to ensure it has been transferred correctly. Check for any discrepancies or errors in the data fields. This step is crucial to maintain data integrity and ensure all records are accurately reflected.
To streamline future imports, consider writing a script that automates the process. This script can extract data from Mailjet, format it, and import it into Convex using the CLI. Schedule this script using a cron job or similar scheduling tool to run at regular intervals, reducing manual intervention and ensuring up-to-date data in Convex.
By following these steps, you can efficiently move data from Mailjet SMS to Convex without relying on third-party connectors or integrations, while maintaining data accuracy and integrity.
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.
Mailjet is one of the affordable software for email marketing campaigns SMS campaigns, newsletter creation, email template building etc. Mailjet permits you to send transactional SMS messages using our Send SMS API. The Mailjet Transactional SMS API offers a straight-forward way to add SMS functionalities to third-party applications. Mailjet's SMS API allows you to send text messages to users around the globe through a simple RESTful API.
Mailjet SMS's API provides access to various types of data related to SMS messaging. The categories of data that can be accessed through the API are as follows:
1. Account data: This includes information about the user's Mailjet SMS account, such as account ID, API key, and account balance.
2. Message data: This includes details about the SMS messages sent and received through the Mailjet SMS platform, such as message ID, sender ID, recipient number, message content, and delivery status.
3. Contact data: This includes information about the contacts or recipients of SMS messages, such as contact ID, phone number, and contact attributes.
4. Campaign data: This includes data related to SMS campaigns, such as campaign ID, campaign name, and campaign statistics.
5. Analytics data: This includes data related to SMS message performance, such as delivery rates, open rates, click-through rates, and conversion rates.
6. Integration data: This includes data related to the integration of Mailjet SMS with other platforms or applications, such as integration ID, integration type, and integration status.
Overall, Mailjet SMS's API provides comprehensive access to data related to SMS messaging, enabling users to track and optimize their SMS campaigns for maximum effectiveness.
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:
