Pump, tank & tap: A framework for near real-time Infor M3 reporting
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At Fortude, we’ve been exploring innovative ways to bring near real-time reporting to businesses using Infor M3 Cloud. One solution our team recently implemented is what we call the Pump, Tank & Tap framework — a simplified way to think about the complex journey of extracting, storing, and visualizing M3 data.
Pump – Getting data out of M3 Cloud
Getting data out of Infor’s multi-tenant cloud isn’t straightforward. For this, you need Infor OS Data Fabric Stream Pipelines — a separate license from your usual M3 Cloud bundle. Think of this as the “pump” that pushes your operational data outside the cloud boundary.
💡 Usage tiers start at around $13K/year excluding cloud egress limits (e.g., 3TB/year on Essentials tier).
Tank – Storing the data
Once out, where do you store the data? Your options include Postgres on Amazon Aurora or Azure, or Snowflake. For our pilot, we chose Azure SQL, which cost us around $3K/year for a basic setup.
💡 We used an “upsert” method instead of traditional inserts — it’s more efficient and ensures you’re always looking at the latest data snapshot.
Tap – Visualizing the data
Finally, it’s time to make the data useful. We tested tools like Power BI and Qlik Cloud, with Power BI outperforming in terms of refresh speed. By building SQL views in our database, we enabled real-time dashboards without needing to wait on pre-modeled data flows.
Overcoming manual setup
Unlike Infor’s built-in ETL tools, Stream Pipelines require manual configuration. But our team automated the toughest parts:
They developed a tool to extract table structures from Infor’s Atlas metadata and load them into Postgres.
We also built an automated flow using our regression testing tool, Fortest, to streamline pipeline creation in Infor OS.
With these tools, we exposed 200+ M3 tables for real-time dashboards — accelerating delivery and improving data access.
It provides a simplified approach to enable near real-time reporting with Infor M3 Cloud, helping businesses extract, store, and visualize operational data efficiently for timely insights and decision-making.
The framework leverages Infor OS Stream Pipelines for data extraction, Azure SQL for storage, and Power BI or Qlik Cloud for visualization. It also uses “upsert” methods and SQL views to maintain data freshness and dashboard performance.
Fortude automated key manual steps by developing tools to extract Infor Atlas metadata and generate Postgres table structures. They also integrated Fortest to streamline pipeline creation in Infor OS, enabling faster setup.