Microsoft Fabric for Manufacturing · Powered by S.C.A.L.E.™
The manufacturing data warehouse, built on Microsoft Fabric for every role that needs it
The board, the plant manager, the field technician on the tablet, the safety officer, the finance analyst on close day, and the auditor - they all need different views of the same truth. Algoscale stands up a governed, role-aware manufacturing data warehouse on Microsoft Fabric - with certified KPIs, RBAC wired to your org chart, and Purview lineage built in.
Works with
AWS 
Azure 
Power BI 
SAP 
Dynamics 
NetSuite 
ServiceNow 
SQL Server Why now
What breaks on the manufacturing floor today
Four problems every CIO and COO in manufacturing recognizes. None of them get fixed by another dashboard - they get fixed by the warehouse underneath.
Plant data trapped in MES silos
Ignition here, Rockwell there, Wonderware at the older plant. Each historian owns its own tag taxonomy. Nothing joins across plants, so group-level reporting is a copy-paste exercise every Monday.
Finance sees last month, ops sees last shift
The close cycle runs monthly. The production schedule runs by the hour. Budget decisions lag shift realities by weeks, and scrap shows up in the P&L long after the line that caused it has moved on.
Quality and production data never meet
First-pass yield lives in the QMS. Throughput lives in the MES. Connecting a defect back to the line, shift, and operator that produced it is a spreadsheet exercise - when it happens at all.
No single view for exec, plant, and regulator
The CEO wants a dollar number. The plant manager wants root causes. The auditor wants lineage. Today that's three reports, three definitions, three sources - and a quarterly argument about which one is right.
KPIs by function
The metrics each role actually asks for
One certified semantic model, six role-specific surfaces. Every metric below is defined once and reused everywhere - so OEE means the same thing to the operator and the CFO.
Operations
OEE (availability × performance × quality) · Downtime by cause code · First-pass yield · MTTR / MTBF. Rolls up from station, to line, to shift, to plant - same model, same definitions.
Safety (HSE)
TRIR and LTIR (both 200,000-hour-normalized per OSHA) · DART rate · Near-miss count · Safety-observation compliance. Auditable lineage back to the EHS source of truth.
Finance
Gross margin · COGS per SKU · Budget vs actual, by plant and by line · Scrap $ · Effective service revenue (MoM Δ) - jobs spanning period-end reconciled via completion-percentage so recognized revenue matches what actually shipped.
Field Service
Technician utilization · First-time-fix rate · SLA attainment · Mean time to repair (installed base) · Billable vs non-billable hours · Travel-to-wrench ratio. Scoped to the jobs and assets a tech is actually dispatched to.
Sales
OTIF (on-time-in-full) · Forecast accuracy · Order-to-delivery lead time · Channel-level margin · Pipeline coverage. Tied back to production signals so the sales number and the ops number agree.
Marketing / Commercial
Product adoption · Price realization · Channel mix · Customer retention by SKU · Share of installed base. The commercial view of the same data the plant is making.
One warehouse, six lenses
Mock-ups of the role-specific views
Same certified model underneath, six Power BI consumers on top. Rendered here inline as illustrations of the shape - your colors, KPIs, and thresholds on delivery.
Operations
- Yield
- 94.2%
- MTTR
- 18 min
Safety
- LTIR
- 0.22
- DART
- 0.36
Finance
- Scrap $ (MTD)
- $184K
- Svc rev MoM Δ
- +$312K
Field Service
- SLA attainment
- 96%
- Billable hrs
- 1,842
Sales
- Pipeline coverage
- 3.1x
- Avg order cycle
- 6.2d
Marketing
- Retention (rolling)
- 92%
- Channel mix shift
- +6pp D2C
Every system the manufacturer runs on
The source inventory we wire up by default
S.C.A.L.E. brings a hardened connector per category - full load on first run, incremental delta after - so the warehouse covers the business, not just the loudest system.
Plant floor (MES / SCADA)
Ignition, Rockwell, Wonderware - historian extracts and live tag streams land in the Bronze layer with standardised tag naming so cross-plant joins finally work.
ERP (SAP / Dynamics / NetSuite)
Production orders, routings, bills of material, budgets, and financial close. Incremental CDC so finance and ops see the same numbers with the same as-of timestamp.
QMS
Non-conformances, CAPAs, lot-level quality tied back to the production event that caused them. Cost-of-poor-quality stops being a guess.
EHS / Safety
Incident logs, near-miss reports, training records, safety observations. Feeds certified TRIR, LTIR, and DART rollups auditable back to the source system.
FSM (Field Service Management)
ServiceNow FSM, Salesforce Field Service, Dynamics FSM. Technician dispatch, job completion, parts movement, and service-revenue recognition on the same timeline as production.
IoT (Azure IoT Hub)
Sensor telemetry via OneLake shortcuts - sub-second into Fabric with no separate OLAP layer. See the Fabric shortcuts vs ADLS mounts decision matrix we use on every migration.
From plant floor to board pack
Raw plant signals flow in through Automated Acquisition, land in a governed medallion lakehouse (Bronze/Silver/Gold), pass through a certified semantic model, and are served to six role-specific consumers. Built on Fabric's F64 capacity model for cost predictability - no pay-per-query surprises. See the full capability in the S.C.A.L.E. product page.
Your enterprise source systems
Owned by you · outside SCALE
SAP ECC / S/4HANA NetSuite 
Salesforce Dynamics 365 / BC ServiceNow SQL Server / Azure SQL Structured Setup
SCALE - the prebuilt, production-ready accelerator
Cloud-Ready Core
- secure, compliant, multi-cloud foundation
AWS
Azure
Standalone Automated Acquisition
- pulls raw data from every source system above
Connectors
SuiteQL · RFC/BAPI · Bulk API · OData · pyodbc
Extraction
Chunked reads · full + incremental · watermarks
Reliability
Retries · backoff · failure alerts
State
DynamoDB · Azure Table · SQLite
Lifecycle Layering
- the data lake medallion + governed pipelines
Bronze
Raw, as landed
Silver
Cleaned, conformed
Gold
Consumption-ready
Execution Engine
- Arcastra™-powered orchestration out to every consumer
Downstream consumers
Served by SCALE · deployed where you need them
Arcastra™ AI agents
- Document Intelligence
- AnalystIQ
- Voice & Chatbot
BI & reporting
- Power BI
- Tableau
- Looker
AI / ML models
- Training data
- Fine-tuning
- RAG pipelines
Reverse ETL
- Hightouch · Fivetran
- Back to operational systems
What we deliver, concretely
Five capabilities every manufacturing warehouse needs
S.C.A.L.E.™ is the delivery vehicle under every engagement - the five capabilities that separate a Fabric warehouse that ships from one that stays in diligence. Each card is a capability we build in by default.
S - Structured Setup
Prebuilt, production-ready lakehouse
C - Cloud-Ready Core
Multi-cloud, secure, compliant
A - Automated Acquisition
Prebuilt connectors, instant ingestion
L - Lifecycle Layering
Medallion pipelines, governed flow
E - Execution Engine
Arcastra™-powered orchestration
Why it matters
RBAC by persona
Access wired to your org chart, not the IT backlog
Five personas, five access scopes. Implemented via Fabric workspace roles, Power BI RLS, Purview sensitivity labels, and Microsoft Entra groups mapped to org hierarchy - so new hires inherit the right view on day one.
Operator / Quality
Station-level signals, defect logging, shift handover notes. No cost or margin data. Read-only on certified views.
Line Supervisor
Shift and line performance - cycle time, yield, WIP, downtime by cause. Cross-line within plant. No executive rollups or cross-plant drill.
Field Service Tech
Mobile-first. Own jobs, assigned installed-base assets, parts inventory at the truck. Cross-region when dispatched. No finance drill-down.
Plant Manager
Plant P&L, scrap $, budget-vs-actual, safety rollups for the site. Cross-line comparisons within the plant. No cross-plant financial drill.
Executive
Cross-plant, cross-region directional dashboards - dollar-denominated, safety and service-revenue rollups. No raw signals or PII.
Findability
Metadata that makes the warehouse discoverable
A data warehouse nobody can find is a data warehouse nobody trusts. Purview and Fabric's catalog do the heavy lifting so analysts stop asking the same question twice.
Certified datasets
OEE, yield, TRIR, service revenue - each metric is defined once in the certified semantic model. Every report, every Copilot prompt, every export reads from the same definition.
Auto-generated lineage
MES tag → Bronze table → Silver dimension → Gold mart → Power BI visual, rendered as a Purview lineage graph. When an auditor asks where a number came from, you show them instead of guess.
Business glossary + Copilot
Fabric Copilot is constrained to certified models only - chat-with-your-data is safe by construction, not by hoping the prompt doesn't pull from a rogue Excel extract.
Compliance, enforced at the infrastructure layer
OSHA safety reporting (TRIR, LTIR, DART auditability), ISO 9001 (quality), ISO 27001 (security), SOX (for public manufacturers), 21 CFR Part 11 (pharma and medical-device), and ITAR / EAR (aerospace, defense). Controls are written into the Terraform that stands the Fabric capacity up - encryption, access boundaries, audit logging, and resource tagging are pipeline output, not documentation. Pairs with Algoscale's data governance consulting, and sits alongside our big data in manufacturing and generative AI in manufacturing practices - the warehouse is the spine they both run on.
Bring your stack
Book a Fabric × manufacturing walkthrough
45 minutes, your source list, your reporting pain. We'll map the warehouse shape and show you what S.C.A.L.E. ships against it.
Keep exploring
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Read morePrefer the long form? Reach out directly.
Bring your source list, your reporting pain, and your org chart. We'll map the warehouse shape and show you what S.C.A.L.E. ships against it on Fabric.