End-to-end forecasting platform from ERP ingestion through medallion data products, feature engineering, MLflow and champion-model deployment to Power BI and Data Agent consumption.
← Explore all 13 architecturesOrganize raw and curated data with quality rules and controlled access.
Illustrative logical architecture. Arrows describe selected relationships, not every network connection. Product alternatives and deployment boundaries are confirmed during design.
For commercial and finance leaders, the goal is better inventory, staffing and revenue decisions. CCS can establish a governed forecasting process that combines trusted historical data with tested models and a clear record of why a forecast changed.
ERP data is ingested and curated before features are prepared. Experiments compare candidate models using time-aware evaluation. An approved model scores new periods and publishes results to business reporting. The consumption layer exposes results for review rather than silently replacing management judgement.
Potential return comes from reduced planning effort and better operational decisions. Improved model accuracy alone is not a financial return; the business must connect the forecast to changes in stock, service or margin.
Baseline → pilot → operational review
Baseline → pilot → operational review
Baseline → pilot → operational review
Include Fabric capacity, data preparation, model maintenance, reporting and business validation.
Recovered time represents capacity, not automatically cash savings. Count it as financial benefit only where finance agrees how that capacity will be used. No achieved client ROI is claimed for this reference architecture.
Enter values in one currency. Gross benefit must reflect achievable adoption and timing. Include all first-year costs; do not count the same benefit twice. These figures stay on this page and are not submitted.
ROI = (gross benefit − operating cost − implementation cost) ÷ (operating cost + implementation cost) × 100. Requires a positive total cost. An estimate, not a forecast or guaranteed return.
Illustrative reference pattern, not a deployable design or a claim of a completed client implementation. CCS validates workload requirements, integrations, security controls, recovery paths and ownership before recommending a production design.
Compare forecasts with a baseline using rolling backtests.
Official guidance behind the design choices. These sources explain technology capabilities; they do not substantiate client returns.
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