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First, log in to your Zoom account and navigate to the "Reports" section. Choose the specific report type you need (e.g., Usage, Meeting, Webinar reports) and select the date range for which you want the data. Once the data is populated, click the "Export" button to download the file in CSV format.
Open your Google Drive and create a new Google Sheets document. This will be the destination for your Zoom data.
Go back to your Google Drive and upload the CSV file you downloaded from Zoom. You can do this by clicking on the "New" button, selecting "File upload," and then choosing the CSV file from your computer.
With the CSV file now uploaded to Google Drive, open it. Google Sheets will automatically open the CSV in a new sheet. You may need to adjust the import settings to ensure that the data is correctly parsed into columns. Click "File" > "Import," choose "Upload," and select the CSV file. Then select the "Replace spreadsheet" option and adjust the delimiter type if necessary.
Review the data in the Google Sheets to ensure it imported correctly. You might need to adjust column widths, format cells for date and time, or clean up any data that didn't transfer perfectly.
Use Google Sheets' built-in tools to sort, filter, and analyze the data as needed. You can create charts, pivot tables, or use formulas to further process the data according to your requirements.
Once your data is organized and analyzed, save your Google Sheets document. You can share it with others by clicking the "Share" button in the top-right corner. Enter the email addresses of those you want to share with and adjust their permissions as needed (e.g., view, comment, or edit).
By following these steps, you can efficiently move data from Zoom to Google Sheets without relying on any third-party tools or connectors.
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.
Zoom offers a communications platform that connects people through video, voice, chat, and content sharing. It has an easy, reliable cloud platform for video and audio conferencing, collaboration, chat, and webinars across mobile devices, desktops, telephones, and room systems. Zoom unifies cloud video conferencing,simple online meetings, and group messaging into one easy-to-use platform. The company's mission is to create a people-centric cloud service that transforms the real-time collaboration experience and improves the quality and effectiveness of communications.
Zoom's API provides access to a wide range of data related to Zoom meetings, webinars, users, and accounts. The following are the categories of data that can be accessed through Zoom's API:
1. Meetings: Information related to Zoom meetings, such as meeting ID, topic, start and end time, duration, participants, and recording.
2. Webinars: Data related to Zoom webinars, including webinar ID, topic, start and end time, duration, attendees, and recording.
3. Users: Information about Zoom users, such as user ID, name, email address, and account type.
4. Accounts: Data related to Zoom accounts, including account ID, name, email address, and billing information.
5. Reports: Various reports related to Zoom meetings and webinars, such as attendance reports, participant reports, and usage reports.
6. Recordings: Information related to Zoom meeting and webinar recordings, including recording ID, name, duration, and download links.
7. Settings: Data related to Zoom account and meeting settings, such as default meeting settings, user settings, and account settings.
Overall, Zoom's API provides a comprehensive set of data that can be used to analyze and optimize Zoom meetings and webinars, as well as manage Zoom accounts and users.
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:
