Import QVD to OleDb Automatically
Need to load QlikView QVD files into a system that supports OLE DB? With Advanced ETL Processor, you can import QVD files into virtually any OLE DB-compatible database - without writing SQL, scripts, or code.
What Is a QVD File?
A QVD (QlikView Data) file is a compressed, structured file format used by QlikView and Qlik Sense. While optimized for Qlik’s engine, QVD files aren’t supported by most databases - which is where Advanced ETL Processor comes in.
What Is OleDb?
Object Linking and Embedding, Database (OleDb) is a Microsoft data access API that allows applications to connect to a wide range of data sources, including SQL Server, Access, Excel, and more. Unlike ODBC, which is limited to relational databases, OleDb also supports non-relational and file-based data.
Why Import QVD via OLE DB?
- Support a wide range of databases and files with one interface
- Use QlikView data in desktop or server applications via OLE DB
- Centralize or convert QVD content into business-ready formats
How to Import QVD to an OLE DB Destination - Step-by-Step
1. Launch Advanced ETL Processor
Open the Enterprise Edition of Advanced ETL Processor. Go to Tools > Connections and set up both the QVD and OLE DB connections.
2. Create a New Transformation
Right-click a transformation group and select New to start a new dataflow.
3. Update Reader Properties
- Drag the QVD Reader onto the canvas
- Double-click it to open the Properties dialog
- Select the appropriate QVD connection
- Choose the QVD file to import
4. Update Writer Properties
- Drag the OLE DB Writer onto the canvas
- Double-click to open the Properties dialog
- Select the correct OLE DB provider and data source
- Choose the destination table or output file (e.g., Access, Excel, SQL Server)
5. Map and Transform Data
Use the AutoMap feature or link fields manually between the QVD Reader and OLE DB Writer. Apply any data transformations like trimming, date formatting, or conversions.
6. Run the Import
Click Execute to run the transformation. Your QVD data will be written to the selected OLE DB destination. Save the transformation for reuse or automation.
7. Automate and Monitor
- Use the built-in scheduler for automated jobs
- Set up triggers based on file drops, time, or external events
- Enable logging, alerts, and rollback support for robust error handling
Where this import fits
Import QVD to OleDb is useful when QVD data needs to feed OleDb, 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 OleDb so reporting teams can query historical Qlik data outside the dashboard layer.
BI migration staging
Move QVD data into OleDb staging tables before validation, reconciliation, and warehouse loading.
Scheduled analytics feed
Import recurring QVD files into OleDb with logs and rejected-row handling instead of manual export steps.
Video Tutorial
FAQ
Can Advanced ETL Processor import QVD to OleDb?
Yes. Advanced ETL Processor can read QVD, map fields, validate data, write to OleDb, 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 OleDb 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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