Eliminating Technical Debt: Retiring Alteryx and Scaling SAP Analytics with Microsoft Fabric
Executive Summary
Vueterra, a premier Mining Supply Chain consulting firm supporting mid-tier Queensland mining companies, had hit a critical operational bottleneck. While their core offerings in SAP Supply Chain implementation and inventory optimization were highly sought after, their internal data architecture was holding them back.
They were heavily reliant on manual Excel/CSV extracts and a cumbersome Alteryx environment. The steep Alteryx learning curve, inability to natively schedule workflows, and client security concerns surrounding the Alteryx SAP DVW connector made it impossible to provide the secure, "plug and play" data platform their enterprise clients demanded. They needed to rapidly modernize their architecture to align with strict IT security policies and build internal team capability for scalable growth.
The Archeon Approach: Results First, Process Later
Vueterra didn't need another expensive enterprise software band-aid; they needed a total architectural reset. Archeon Consulting executed a targeted shift toward a Microsoft Modern Data Warehouse tailored for SMBs.
We completely bypassed the limitations of their existing stack by designing a scalable, Azure-secured ecosystem. By strategically utilizing Azure Data Factory for robust SAP integration and deploying a Fabric Lakehouse architecture, we set the foundation to effortlessly handle future AI advancements without locking them into rigid, legacy patterns
The Challenges
Challenge 1: The Alteryx Bottleneck & Security Vulnerabilities
The Issue: Vueterra's data transformation relied entirely on Alteryx workflows that were notoriously difficult to debug, lacked version control, and posed security red flags for clients due to the DVW analytics connector.
TheArcheon Fix: Total Refactor & Modern Analytics Engineering. We completely discontinued the Alteryx licenses. In its place, we adopted a software-engineering approach, migrating all transformations into PySpark notebooks and leveraging dbt combined with Azure DevOps. This introduced modular, DRY (Don't Repeat Yourself) code, automated testing, and robust Git version control into their daily operations.
Challenge 2: Ingesting Complex SAP Data at Scale
The Issue: Extracting data from SAP S4/HANA and ECC6 systems was manual, highly complex, and lacked automated scheduling.
TheArcheon Fix: Automated Azure Data Factory Pipelines. Because Fabric Data Factory couldn't support the required SAP connectors, we engineered automated ingestion pipelines using Azure Data Factory. This provided fit-for-purpose SAP data connectors and metadata-driven ingestion capabilities, establishing daily delta loads directly into an immutable Bronze Lakehouse layer.
Challenge 3: Siloed Reporting and Sluggish Dashboard Performance
The Issue: Without a unified data lake, dashboards were slow, and metrics were disconnected across various SharePoint sites and SQL servers.
TheArcheon Fix: OneLake & Direct Lake Mode. We unified their data estate on OneLake and utilized Fabric Direct Lake mode. By loading massive volumes of Delta table data directly into memory, we achieved blazing-fast query performance and dashboard load times without duplicating data. Furthermore, we upgraded their dashboards with native "Time Travel" capabilities, allowing the team to instantly query historical data versions for audits.
The Business Impact & Unmatched Velocity
Archeon delivered a complete platform overhaul at an aggressive pace. Within Month 1, we developed and scheduled fully automated ADF data ingestion pipelines.
By Month 2, we successfully ingested 64 highly complex SAP ECC tables into the Bronze layer.
By the end of Month 3, we had successfully migrated and refactored every single legacy Alteryx workflow into a modern Lakehouse architecture. We deployed 20 Silver models, engineered 58 Gold models, and flawlessly repointed 29 client dashboards to the new, highly performant architecture. Finally, we secured a 48% discount on their Fabric Compute tier via a strategic 12-month reservation, drastically reducing their operational overhead.
Services Provided
Services Provided
Modern Data Strategy & Platform Modernization
Total architectural redesign; technical audit of legacy Alteryx environment; Fabric capacity planning (securing a 48% reservation discount).
Microsoft Fabric & Azure Data Factory Engineering
Deployment of automated ADF pipelines for daily SAP delta loads; ingestion of 64 complex SAP ECC tables; implementation of Medallion Lakehouse architecture (Bronze, Silver, Gold).
Analytics Engineering (dbt & PySpark)
100% migration of Alteryx workflows to PySpark; engineering of 20 Silver models and 58 Gold models; enablement of Delta table "Time Travel" for historical querying.
CI/CD & DevOps Integration (Azure DevOps)
Integration of Azure DevOps Git with Microsoft Fabric; deployment of a modular dbt framework; establishment of version-controlled daily coding processes.
Technology Stack
SAP ECC
Primary ERP environment storing mission-critical supply chain data. The chosen architecture is highly extensible and natively accommodates future data ingestion use cases, including Dynamics 365, Dataverse, and Synapse Link.
Azure Data Lake Storage Gen 2 + One Lake Shortcuts
Unified, ACID-compliant and highly scalable data storage conforming to Azure security best practices, enabling Direct Lake mode for blazing-fast Power BI query performance. OneLake shortcuts also eliminate unnecessary data duplication across medallion layers.
Fabric Lakehouse
Highly scalable and industry-standard medallion architecture built on top of Lakehouse Delta Tables, enabling time travel and Direct Lake mode for blazing-fast Power BI query performance.
Apache Spark + dbt
Replaced rigid Alteryx workflows with a code-first, software engineering approach. Utilizing dbt Cloud acts as a core enabler for modularity. This establishes a highly scalable foundation which future proofs the platform by providing the ability to rebuild the platform instantly in another data warehouse such as Databricks.
Fabric Data Pipeline
Leveraged out of the box Fabric Data Pipelines to enable highly reliable scheduling, monitoring, and orchestration of PySpark notebooks and data transformation workflows.
Azure DevOps
Provided enterprise-grade version control and automated deployments. Syncing Azure DevOps repositories directly with Fabric workspaces ensured strict environment isolation and completely eradicated code contamination.