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Begin by logging into your Lokalise account. Navigate to the project from which you want to export data. Click on the "Download" or "Export" option, typically located in the top menu. Choose your preferred file format for export, such as CSV or JSON, and download the file to your computer. Make sure to select the appropriate languages and settings according to your needs.
Access Google Sheets by logging into your Google account and opening Google Drive. From there, click on "New" and select "Google Sheets" to create a new spreadsheet. Alternatively, open an existing spreadsheet if you wish to add the Lokalise data to it.
In your Google Sheets document, decide where you want to place the data. You may want to label your columns in the first row to match the data fields in your Lokalise export. This will help keep your data organized and easy to understand.
Use a text editor like Notepad (Windows), TextEdit (Mac), or any code editor to open the exported file from Lokalise. This allows you to view the data structure and format, particularly important if you need to make any adjustments before importing it into Google Sheets.
If your exported file is in CSV format, it is generally ready for import. However, if it's in JSON or another format, you may need to convert it to CSV. You can do this manually by copying the relevant sections of data into a new CSV file or using built-in functions in your text editor to reformat the data.
In Google Sheets, click on "File" in the top menu, then select "Import." Choose "Upload" and drag your CSV file into the upload area, or select it from your computer. In the import settings, choose "Replace current sheet" or "Insert new sheet(s)" depending on your preference. Click "Import Data" to complete the process.
Once your data is in Google Sheets, review it to ensure everything imported correctly. Check for any discrepancies or formatting issues that may have occurred during the import process. Clean up any unnecessary data, adjust column widths, and apply any formatting to enhance readability and usability.
By following these steps, you can efficiently transfer data from Lokalise to Google Sheets 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.
Using Lokalise, you can manage your localizations in an easy, affordable, and modern way. It is a cloud-based system that allows you to manage localizations and translations efficiently. Especially when utilizing the continuous localization capabilities, it makes your website, app, game, or any other project global, vibrant, and engaging. The tool localise belongs to the Translation Service category. You need a platform that brings together all stakeholders and processes to make localization successful.
Lokalise's API provides access to a wide range of data related to localization and translation management. The following are the categories of data that can be accessed through Lokalise's API:
1. Projects: Information related to the projects created in Lokalise, including project ID, name, description, and project settings.
2. Keys: Data related to the keys used in the localization process, including key ID, name, description, and translation status.
3. Translations: Information related to the translations of the keys, including translation ID, language, and translation text.
4. Teams: Data related to the teams working on the localization projects, including team ID, name, and team members.
5. Files: Information related to the files used in the localization process, including file ID, name, and file format.
6. Comments: Data related to the comments made on the keys and translations, including comment ID, author, and comment text.
7. Tags: Information related to the tags used to categorize the keys and translations, including tag ID, name, and tag color.
Overall, Lokalise's API provides comprehensive access to the data required for efficient localization and translation management.
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:
