Your SAP Has the Data.
Your Reports Don't Show It.

Yes. SAP B1 exposes data through the Service Layer API (a RESTful OData API) and through direct HANA or SQL database access, depending on your deployment. We typically use the Service Layer for real-time or near-real-time connections, and direct database access for historical loads and complex cross-module queries. The approach depends on your B1 version, deployment model (cloud vs on-premise), and what data volumes you're working with.

Yes. S/4HANA exposes data through OData services and CDS views, and Microsoft Fabric can consume both via Azure Data Factory connectors and the Fabric pipeline layer. The extraction strategy depends on whether you're doing real-time operational reporting (use OData with delta tracking) or batch analytics (use CDS view extraction into the Fabric lakehouse). We design the architecture based on your refresh requirements and the specific S/4 modules in scope.

SAP's native reporting (Fiori apps, Crystal Reports in B1, standard S/4 reports) is optimised for transaction-level and module-level reporting. It does not do cross-module analytics, custom KPI definitions, role-based dashboards for non-SAP users, or the kind of trend analysis and visualisation that operations directors and CFOs actually want to look at. Power BI on top of SAP gives you both: the governed, auditable transactional data from the ERP, and the analytical layer that makes it useful to the business.

A SAP to Power BI integration delivers first value in 6 weeks and reaches production at 8 weeks — a governed pipeline from your SAP system into Microsoft Fabric with live Power BI dashboards. A 2-week Starter Sprint that proves one SAP source is the faster entry point. Larger S/4HANA estates with many modules can extend beyond 8 weeks, scoped after a short discovery.

Yes. Custom fields, user-defined tables, and non-standard configurations are where SAP analytics consulting actually earns its cost — the out-of-the-box connector doesn't know your cost centre structure, your custom item attributes, or your locally-developed add-ons. We spend the first phase of every SAP integration mapping your specific configuration, not assuming a standard implementation.

The SAP B1 Service Layer is a RESTful OData API that exposes Business One objects — orders, invoices, items, business partners — for governed extraction. We connect it through Azure Data Factory or Fabric pipelines to land B1 data in OneLake, then report in Power BI on Direct Lake. It gives near-real-time data without touching the B1 database directly.

We map each Crystal Report to its underlying B1 tables and rebuild it as a governed Power BI model — cross-module, refreshable, and shareable to non-SAP users. B1 data flows via the Service Layer or database into OneLake, so the reports stop being static documents and become live dashboards. Crystal stays only where a pixel-perfect statutory layout requires it.

Land purchasing, inventory, and finance tables from B1 into OneLake, conform them to shared keys in the silver layer, and model the cross-module measures in gold. Because the modules join on one governed model, you can report margin, stock cover, and spend together — something B1's module-level reports cannot do. Power BI on Direct Lake keeps it current.

Connect the B1 Service Layer (OData) or its database via Azure Data Factory with incremental extraction, landing changes in OneLake continuously rather than a nightly CSV dump. Power BI on Direct Lake then reads live data with no refresh window. The manual export step — and the errors it introduces — disappears.

Power BI connects to SAP S/4HANA through OData services and CDS views, consumed by Azure Data Factory or Fabric pipelines and landed in OneLake. Delta tracking pulls only changed records, so extraction stays light on the production system. Power BI on Direct Lake then reports current S/4 data without CSV exports.

Delta extraction pulls only the records changed since the last run — via OData delta tokens, CDS view extraction, or CDC — rather than a full reload each time. In Microsoft Fabric, the changes land in the bronze layer and merge through silver, keeping the lakehouse current and the SAP load minimal. It is what makes near-real-time S/4 reporting practical.

We extract the operational data BW/4HANA serves — via OData, CDS views, or direct extraction — into OneLake, and rebuild the KPIs as a governed Power BI model. For operational reporting this removes a heavy layer and gives faster, self-service dashboards on Direct Lake. BW/4HANA can stay for the statutory and finance workloads it suits; Power BI takes the operational front end.

Extract PP (production), MM (materials), SD (sales), and FI/CO (finance) data into OneLake and conform them to shared keys — material, plant, order — in the silver layer. The gold model then joins them so one dashboard shows production, stock, sales, and cost together. That cross-module view is exactly what standard SAP reports cannot give an operations director.

SAP Fiori analytics is strong for transaction-level, in-context insight inside SAP, for SAP-licensed users. Power BI is stronger for cross-module analytics, custom KPI definitions, role-based dashboards for non-SAP users, and trend visualisation the business actually consumes. Fiori answers "what is this order doing"; Power BI answers "how is the plant performing this month". Most operations leaders need the Power BI layer on top of the governed S/4 data.

Extract the invoice, tax, and master data S/4HANA holds into OneLake, then build Power BI reports that reconcile issued invoices against ZATCA submission status and flag exceptions. The governed model gives finance one auditable view of compliance rather than manual spreadsheet checks. We confirm scope against your ZATCA phase and SAP configuration.

SAP Business ByDesign exposes data through its OData and analytics APIs and custom OData reports, which Azure Data Factory or Fabric pipelines extract into OneLake — no ABAP. Data conforms through silver and surfaces as governed Power BI datasets on Direct Lake. This stays within standard ByD licensing and survives tenant updates.

Extract each ByDesign tenant through its OData APIs into the same OneLake lakehouse, then conform them to shared keys so entities, currencies, and charts of accounts align in the silver layer. One gold model then reports across all tenants as a single group view. Power BI on Direct Lake shows consolidated and per-tenant figures from one source.

Extract ByDesign project, cost-centre, and financials data via OData into OneLake, conform it in silver, and model project margin, cost-to-complete, and cost-centre spend in gold. Power BI then gives project and finance leaders live analytics that ByDesign's built-in reports cannot assemble. It reconciles to the ledger because it reads governed ByD data.

ByDesign's built-in reports are tenant-scoped, module-bound, and limited in cross-entity analytics, custom KPIs, and visualisation. We overcome them by extracting ByD data via OData into a governed OneLake model, then building cross-module and multi-tenant dashboards in Power BI. The ERP keeps the transactions; Power BI provides the analytics layer.

SAP's native reports are built for transactions and single modules, not for the cross-module, trend-based, role-specific view an operations director needs at 8am. The data is governed and correct — it is just locked in a format built for processing, not decisions. Power BI on top turns that governed SAP data into the dashboards operations actually uses.

Extract SAP sales (SD) and inventory (MM) data into OneLake via OData or Mirroring, conform it in silver, and model fill rate, stock cover, and sales by SKU in gold. Power BI on Direct Lake then shows live sales and inventory together, not a nightly extract. FMCG planners act on current numbers across SKU and region.

Yes — it is one of the most common SAP estates we work in. The data lives across SAP SD (delivery), MM (materials), and LE (logistics execution): deliveries, shipments, transport costs, goods movements. The problem is rarely missing data — it is that OTIF and DIFOT get calculated three ways in three spreadsheets and freight cost arrives a month late. We extract those modules through Azure Data Factory into a Fabric lakehouse, conform them into one governed model, and build OTIF, DIFOT, on-time despatch, and freight-cost-per-shipment as live Power BI dashboards a logistics head can act on at the shift handover. Where SAP TM or an external WMS runs alongside ECC, we bring those in through the same pipelines.

Manual Excel reporting exists because getting data out of SAP is slow — so people export, paste, and reconcile by hand. A governed pipeline from SAP into OneLake and Power BI removes the export step: the numbers are current, defined once, and shared automatically. The hours spent rebuilding the same workbook each week go away.

A live SAP system holds rich operational and financial data, but most of it never reaches a decision because it sits behind transaction-level, module-bound reports. The value is not missing — it is locked in a format built for processing, not analysis. A governed Power BI layer on top of SAP is what releases it, typically replacing weeks of manual reporting with live dashboards.

A SAP to Power BI integration for a mid-market manufacturer is typically USD 5,000-8,000, delivering first value in 6 weeks and production at 8. A 2-week Starter Sprint that proves one SAP source in Power BI starts at USD 1,500. SAP licensing and Fabric capacity are separate; we confirm the fixed fee after a 30-minute diagnostic.

Microsoft Fabric connects to SAP through Azure Data Factory's SAP connectors — SAP Table, SAP OData, SAP BW/BW4, SAP HANA, and SAP ECC — plus the B1 Service Layer and ByDesign OData APIs. Choice depends on the SAP product and whether you need real-time or batch. All routes land data in OneLake as Delta for Power BI.

SAP ECC predates the clean APIs of S/4HANA, so the connector choice matters. Azure Data Factory ships the ones that do this: the SAP Table connector (RFC-based, for direct extracts like VBAK, MARA, MSEG), the SAP CDC connector for change-data-capture delta loads, the SAP BW Open Hub connector where ECC already feeds BW, and the SAP HANA and OData connectors where those endpoints exist. They run through a self-hosted integration runtime next to your SAP landscape, with the SAP .NET connector (NCo) on the RFC path — no custom ABAP for most extractions. Data lands in OneLake as Delta, conforms through the medallion layers, and surfaces in Power BI.

Where the SAP database is supported, Fabric Mirroring replicates it into OneLake continuously, giving a near-real-time analytical copy without extract pipelines. Power BI on Direct Lake then reports live SAP data with no refresh window. Where Mirroring is not available for a given SAP source, OData with delta tracking is the near-real-time alternative.