Import QVD to Saleforce Automatically
Connecting QlikView QVD files to Salesforce typically requires custom development or API scripting. With Advanced ETL Processor, you can automate QVD-to-Salesforce integration - no code, no Apex, and no external connectors required.
What Is a QVD File?
A QVD (QlikView Data) file is a high-performance, compressed format used by QlikView and Qlik Sense to store structured data. QVDs are not natively supported by Salesforce, which makes an ETL tool essential for integration.
What Is Salesforce?
Salesforce is a leading cloud-based CRM and business platform used by enterprises worldwide to manage sales, support, marketing, and customer data. It supports custom objects, APIs, and integrations via tools like SOQL, Apex, and REST.
Why Import QVD into Salesforce?
- Sync QlikView insights with Salesforce accounts, leads, or custom objects
- Combine BI data with CRM workflows, dashboards, and automation
- Eliminate manual data entry and improve data consistency
How to Import QVD to Salesforce - Step-by-Step
1. Launch Advanced ETL Processor
Open the Enterprise Edition of Advanced ETL Processor. Go to Tools > Connections and configure connections for both QVD and Salesforce (you’ll need your Salesforce credentials and API token).
2. Create a New Transformation
Right-click on a transformation group and choose New to start building a new dataflow.
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 Salesforce Writer onto the canvas
- Double-click to open the Properties dialog
- Select the appropriate Salesforce connection
- Choose the Salesforce object (e.g., Lead, Account, Opportunity, or custom object)
5. Map and Transform Data
Use the AutoMap feature or manually link fields from the QVD source to Salesforce fields. You can apply transformations like formatting, mapping values to picklists, or handling lookups via IDs.
6. Run the Import
Click Execute to upload your QVD data to Salesforce. You can save the transformation for reuse or schedule it for automated updates.
7. Automate and Monitor
- Schedule regular QVD-to-Salesforce imports using the built-in scheduler
- Trigger updates based on file changes, time, or system events
- Enable logging, failure alerts, and rollback functionality
Where this import fits
Import QVD to Saleforce is useful when QVD data needs to feed Saleforce, 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 Salesforce so reporting teams can query historical Qlik data outside the dashboard layer.
BI migration staging
Move QVD data into Salesforce staging tables before validation, reconciliation, and warehouse loading.
Scheduled analytics feed
Import recurring QVD files into Salesforce with logs and rejected-row handling instead of manual export steps.
Video Tutorial
FAQ
Can Advanced ETL Processor import QVD to Saleforce?
Yes. Advanced ETL Processor can read QVD, map fields, validate data, write to Saleforce, 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 Saleforce 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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