Back to all BlogsHow AnalyticsCreator Enables Easy Data Exports with Azure Data Factory & SSIS
The newest version of AnalyticsCreator lets you generate export pipelines and packages — using Azure Data Factory or SSIS — to send data from your warehouse into cloud services, analytical databases, data lakes, ML platforms, or even back to source systems.
With the latest update, AnalyticsCreator supports generating Azure Data Factory pipelines and SSIS packages that export data from your data warehouse to a wide variety of target systems — from cloud stores to analytical databases to planning or ML platforms.
Flexible Export Options with ADF and SSIS
AnalyticsCreator allows export to any external database or storage target using standard OLEDB or ODBC drivers. You can also export to CSV or text files, or directly to cloud storage such as Azure Blob Storage — whichever target your external system supports.
What You Can Achieve
- Create a data lake in Azure or other cloud environments
- Export data into files (CSV, text) and load them into services like BigQuery, AWS, or other cloud data lakes
- Export data marts into analytical databases such as Snowflake, Teradata, or specialized analytics platforms
- Feed data into planning or financial tools like Acterys, IBM Planning Analytics, or LucaNet
- Send data to machine‑learning or AI platforms — within Azure or other databases for AI/ML workflows
- Push transformed or calculated data back into source systems so your applications can use clean data directly
For a demonstration of this export functionality in action, watch our video on the AnalyticsCreator YouTube channel: New connector for exporting data from data warehouse to many target systems
Frequently Asked Questions
What export options does AnalyticsCreator support?
It supports exporting via Azure Data Factory pipelines, SSIS packages, OLEDB/ODBC drivers, and can output to CSV/text files or cloud storage (e.g. Azure Blob).
Can I export to cloud data lakes or external data warehouses?
Yes. You can export to cloud data lakes, analytical databases, or external warehouses like Snowflake, Teradata, or cloud‑native stores.
Is export limited to read‑only data?
No. You can also export transformed or calculated data back to source systems, enabling write‑back or integration with client applications and planning tools.
Can I use this for ML/AI or planning tools?
Absolutely. With support for exporting to cloud storage or analytical databases, you can feed data directly into ML platforms, planning solutions, or analytics engines.
What if my target system only accepts CSV or similar formats?
Yes, this module integrates smoothly with any AnalyticsCreator can export to CSV or text files, which you can then load into target systems via their native ingestion processes.
Does this require special drivers or configurations?
As long as the target system supports a standard OLEDB or ODBC driver (or file‑based ingestion), the export will work and AnalyticsCreator handles the generation.
Is this suitable for data lakes and cloud‑native architectures?
Yes. This export functionality supports cloud storage and export to cloud data lakes, enabling modern, scalable architectures.
How do I get started with export using AnalyticsCreator?
Use the latest version of AnalyticsCreator, define your target configuration (driver or file/cloud), and generate the ADF pipeline or SSIS package and then deploy as needed.
