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Strategic Impact
Our Approach
SAP Data Structure Review & Pipeline Architecture
Available SAP BAPI extraction methods were reviewed, reporting requirements were scoped with the operations team, and a target architecture was defined covering the SQL Server staging layer and Power BI semantic model design.
Python SAP Extraction Pipeline Build
Python scripts were built to connect to SAP via BAPI, extract the required financial and operational data, and load records into a SQL Server staging database on a scheduled basis.
Data Validation & Source Reconciliation
Extracted data was validated against SAP source figures across multiple periods to confirm extraction accuracy before any reporting was built on top of the data layer.
Power BI Dashboard Build & Delivery
Power BI dashboards were built on top of the SQL data layer covering financial performance, operational KPIs, and period-over-period comparisons, validated with the operations team before final delivery.
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Report Sign-Off & Operational Handover
Completed dashboards were reviewed and signed off by the client's operations team, and the extraction pipeline was handed over with documentation covering scheduling, error handling, and the data model structure.
BabyBots Impact Assessment
The Impact
The energy services company's leadership gained reliable, current financial and operational reporting drawn directly from SAP without manual extraction. The pipeline runs on schedule and the dashboards reflect current figures, removing the bottleneck that had made reporting dependent on a small number of individuals who understood the source system.
- Python-based SAP BAPI extraction scripts for financial and operational data
- SQL Server staging database with validated data load
- Power BI dashboards for financial performance and operational KPIs
- Scheduled extraction pipeline with error handling
- Data model documentation and operational handover guide
Project Journey
Project Timeline
Phase 1
Energy BI & SAP Extraction — Requirements & Architecture (Phase 1)
Reviewed SAP BAPI data structures and available extraction methods, scoped the pipeline requirements, and designed the SQL Server and Power BI target architecture.
Phase 2
Energy BI & SAP Extraction — Pipeline Build & Data Load (Phase 2)
Built Python-based data extraction scripts connecting to SAP, loaded data into SQL Server, and validated extract accuracy against source figures.
Phase 3
Energy BI & SAP Extraction — Power BI Build & Delivery (Phase 3)
Built Power BI dashboards on top of the SQL layer, delivered financial and operational reporting, and validated report accuracy with the client's operations team.
Networks / Energy Services
SAP Data Extraction & Power BI Reporting for an Energy Services Company
Completed dashboards were reviewed and signed off by the client's operations team, and the extraction pipeline was handed over with documentation covering scheduling, error handling, and the data model structure.
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BabyBots is an enterprise technology partner with expertise across process automation, AI systems, data intelligence, and platform architecture.
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