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Begin by logging into your Monday.com account. Navigate to the board from which you wish to export data. Click on the three-dot menu in the upper right corner of the board view and select "Export to Excel". This will download the board's data as an Excel (.xlsx) file to your computer.
Locate the downloaded Excel file on your computer. Open the file using Microsoft Excel or any compatible spreadsheet software. This file contains all the data from your Monday.com board in a structured format.
Before importing the data into Google Sheets, review the Excel file to ensure all the necessary data is present and correctly formatted. Make any required changes, such as adjusting column headers, correcting data types, or removing unnecessary columns and rows.
Open your web browser and go to Google Sheets (sheets.google.com). Sign in with your Google account if you are not already logged in. You will be directed to the Google Sheets dashboard.
From the Google Sheets dashboard, click on the "Blank" option to create a new spreadsheet. This will open a new, untitled Google Sheet where you can import your data.
In your new Google Sheet, click on "File" in the top menu, then select "Import". In the Import dialog, choose "Upload" and drag your Excel file into the window or click "Select a file from your device" to locate your file manually. Once uploaded, choose the option to "Replace spreadsheet" to import the data into your Google Sheet.
After the import is complete, review the data in Google Sheets to ensure it has been imported accurately. Verify that all columns and rows appear as expected. Make any necessary adjustments to formatting, formulas, or data organization to suit your needs. Save your Google Sheet by clicking "File" and then "Save" or simply closing the tab, as Google Sheets automatically saves changes in real-time.
By following these steps, you can successfully move data from Monday.com to Google Sheets manually, without relying on third-party tools 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?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
