Import QVD to Google Spreadsheet Automatically
Need to make QlikView QVD data accessible in Google Sheets for sharing, analysis, or collaboration? Advanced ETL Processor allows you to import QVD files directly into Google Spreadsheets - no scripting, no APIs, and no manual exports required.
What Is a QVD File?
A QVD (QlikView Data) file is a fast, structured data format used by QlikView and Qlik Sense. It's highly efficient for BI tools but not directly supported by spreadsheet platforms like Google Sheets.
What Is Google Sheets?
Google Sheets is a cloud-based spreadsheet application that enables collaborative data editing, real-time sharing, and reliable integration with other Google Workspace tools. It is widely used for dashboards, reporting, and data collection.
Why Import QVD into Google Sheets?
- Share QlikView data with business users who prefer spreadsheets
- Visualize QVD data with charts, filters, and pivot tables in Google Sheets
- Integrate Qlik insights into collaborative reports, forms, or dashboards
How to Import QVD to Google Sheets - Step-by-Step
1. Launch Advanced ETL Processor
Open the Enterprise Edition of Advanced ETL Processor. Go to Tools > Connections and configure both your QVD source and Google Sheets destination (using Google API credentials).
2. Create a New Transformation
Right-click on a transformation group and click New to create a new dataflow project.
3. Update Reader Properties
- Drag the QVD Reader onto the canvas
- Double-click to open the Properties dialog
- Select the appropriate QVD connection
- Choose the QVD file to import
4. Update Writer Properties
- Drag the Google Sheets Writer onto the canvas
- Double-click to open the Properties dialog
- Select your Google account connection
- Choose the spreadsheet and sheet name where the data will be written
5. Map and Transform Data
Use AutoMap or manually map the fields between the QVD source and the Google Sheet. You can also apply transformations like formatting, formulas, or calculated fields if needed.
6. Run the Import
Click Execute to send the QVD data directly into your chosen Google Sheet. You can save and reuse this transformation anytime.
7. Automate and Monitor
- Use the built-in scheduler to refresh the data at set intervals
- Trigger imports on file creation, schedule, or event-based logic
- Enable logging and email notifications for job success or failure
Where this import fits
Import QVD to Google Spreadsheet is useful when QVD data needs to feed Google Spreadsheet, reporting databases, operational systems, migration jobs, or downstream ETL workflows. Use it when the same import needs validation, mapping, transformations, scheduling, and logs instead of another manual load.
Do not automate the import until the source layout, target table, key fields, write mode, and failure behaviour are agreed. Automation repeats rules; it does not rescue unclear ones.
Useful links for this import
Start with the Advanced ETL Processor Enterprise overview, then download the fully functional 30-day trial. The import-data hub lists the other QVD import workflows.
Business usage examples
Qlik reporting archive
Load QVD extracts into Google Sheets so reporting teams can query historical Qlik data outside the dashboard layer.
BI migration staging
Move QVD data into Google Sheets staging tables before validation, reconciliation, and warehouse loading.
Scheduled analytics feed
Import recurring QVD files into Google Sheets with logs and rejected-row handling instead of manual export steps.
Video Tutorial
FAQ
Can Advanced ETL Processor import QVD to Google Spreadsheet?
Yes. Advanced ETL Processor can read QVD, map fields, validate data, write to Google Spreadsheet, and log the import.
Do I need to write scripts for the import?
No scripting is required for the normal import workflow. You can configure the reader, writer, mapping, validation, and schedule visually.
Can the QVD import run on a schedule?
Yes. The package can run on a schedule, process matching QVD files, archive originals, and write rows to Google Spreadsheet with the same validation rules each time.
Can imported data be transformed before loading?
Yes. You can clean values, convert data types, calculate fields, split columns, and apply lookup rules before writing to the target.
Can bad rows be logged or rejected?
Yes. Add validation rules so rejected rows, failed files, row counts, and error details are visible after each run.
What should I check before the first production import?
Check source layout, target table, key fields, data types, date formats, write mode, archive folder, and failure handling.
When should I not automate the import yet?
Do not automate it until the source layout, target table, key fields, and bad-row handling are clear. Automation repeats rules; it does not invent them.
Can I test the import before buying?
Yes. Download the fully functional 30-day trial, build one small import, and test it with a deliberately awkward sample file.
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