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To begin, manually export the data from Monday.com. Log into your Monday.com account and navigate to the board containing the data you wish to export. Use the export feature (usually found under board settings) to download the data in a CSV format. Save this file locally on your computer.
Ensure you have an AWS account. Navigate to the AWS Management Console and create an S3 bucket if you haven't already. This bucket will store your Monday.com data. Make sure to configure the necessary permissions and access policies to allow data upload and access.
Using the AWS Management Console, upload your exported CSV file to your S3 bucket. Navigate to the S3 service, select your bucket, and use the "Upload" button to add your CSV file. Confirm that the file is correctly uploaded and accessible.
Go to the AWS Glue console and set up a new Glue Crawler. This will help you catalog the data in your S3 bucket. Define a new data source pointing to your S3 bucket and configure the crawler to create a new database or use an existing one. Run the crawler to populate the Glue Data Catalog with your CSV data schema.
Once the data is cataloged, create a new ETL (Extract, Transform, Load) job in AWS Glue. Specify the data source (your S3 bucket and cataloged data) and define the target where you want the transformed data to be stored. You can use the Glue ETL script editor to modify the data if needed.
Execute the Glue ETL job by selecting the job from the Glue console and choosing "Run Job." Monitor the job's progress through the console to ensure it completes successfully. Any errors or logs will be available for troubleshooting if needed.
Once the ETL job is complete, verify that the transformed data is stored correctly in the specified S3 bucket. Use the AWS S3 console to navigate to your bucket and check the contents. Ensure that the data is in the desired format and structure needed for your use case.
By following these steps, you can effectively transfer and transform your data from Monday.com to AWS S3 and Glue 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.
Monday is the first day of the week in most countries and is typically associated with the start of a new work or school week. It is often viewed as a day of productivity and setting goals for the week ahead. Many people may feel a sense of dread or stress on Mondays, commonly referred to as the "Monday blues." However, others may view it as an opportunity to start fresh and tackle new challenges. Some cultures also have specific traditions or superstitions associated with Mondays, such as avoiding certain activities or wearing specific colors. Overall, Monday represents a new beginning and a chance to make the most of the week ahead.
Monday's API provides access to a wide range of data related to project management and team collaboration. The following are the categories of data that can be accessed through Monday's API:
1. Boards: This category includes data related to the boards created in Monday, such as board name, description, and status.
2. Items: This category includes data related to the items created within a board, such as item name, description, and status.
3. Users: This category includes data related to the users who have access to a board, such as user name, email address, and role.
4. Groups: This category includes data related to the groups created within a board, such as group name, description, and members.
5. Columns: This category includes data related to the columns created within a board, such as column name, type, and settings.
6. Updates: This category includes data related to the updates made to a board or item, such as update text, creator, and timestamp.
7. Notifications: This category includes data related to the notifications sent to users, such as notification type, recipient, and timestamp.
Overall, Monday's API provides access to a comprehensive set of data that can be used to build custom integrations and applications to enhance project management and team collaboration.
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?
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