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To begin the process, you need to export your data from Monday.com. Go to the board or workspace you want to export. Click on the three-dot menu on the top right corner of your board, select "Export board to Excel" or "Export board to CSV." This will download your data into a file format that can be manipulated and prepared for loading into Starburst Galaxy.
Once you have your data in an Excel or CSV file, open it with a spreadsheet application like Microsoft Excel or Google Sheets. Review the data to ensure all necessary information is included and clean up any inconsistencies or errors. Ensure that your data is structured properly, with clear headers and consistent data types, as this will facilitate the import process into Starburst Galaxy.
After preparing your data, save the cleaned file in a format that is compatible with Starburst Galaxy, such as CSV or Parquet. If your data requires conversion to Parquet format, you can use tools like Apache Arrow or Python libraries such as Pandas with pyarrow to convert CSV files to Parquet.
Log in to your Starburst Galaxy account. If you don't have an account, you will need to sign up and set up your environment before proceeding. Familiarize yourself with the Starburst Galaxy interface, particularly the data import and user management sections.
Starburst Galaxy requires data to be stored in a cloud storage service like Amazon S3, Google Cloud Storage, or Azure Blob Storage. Upload your prepared CSV or Parquet file to a bucket in your cloud storage service. Ensure you have the necessary permissions to access and manage the data in this storage location.
In Starburst Galaxy, create a catalog that connects to your cloud storage. This involves configuring the catalog with the necessary connection details and credentials. Once the catalog is set up, create a schema within the catalog to organize your tables. This schema acts as a namespace to contain your imported data tables.
Finally, use SQL commands in Starburst Galaxy to load your data from the cloud storage into the catalog and schema you created. Use a CREATE TABLE AS SELECT (CTAS) statement or similar SQL commands to load the data. Verify the data import by running a few SELECT queries to ensure the data has been loaded correctly.
By following these steps, you should be able to transfer your data from Monday.com to Starburst Galaxy without relying on any 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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