Pipeline stages
8
Platform demo · Fabric readiness
OneLake path: lakehouse → warehouse → semantic → report
Click through curated stages and quality checks that precede Copilot—trust and semantic contract before Fabric sprawl. Synthetic manufacturer facts only.
How this maps to Microsoft Fabric
Microsoft Fabric consulting and readiness for mid-market teams.
- Clickable OneLake-style stage canvas
- Quality events feeding trust badges
- Shortcut vs materialize row-count toggle
- Pragmatic staging: Power BI-quality model before Fabric sprawl
Related consulting page → · All platform demos · Book My BI Diagnostic
OneLake path: lakehouse → semantic → report
Click stages to inspect latest pipeline runs and trust checks.
Quality fails
$6,007
Latest run rows
$3,039
Lens chart A
Lens chart B
Pipeline / job stages
- bi_dataset_publish · adf · succeeded · 593s · 3,039 rows
- bi_dataset_publish · adf · succeeded · 273s · 3,265 rows
- bi_dataset_publish · adf · succeeded · 254s · 1,888 rows
- semantic_refresh · adf · succeeded · 458s · 6,498 rows
- semantic_refresh · adf · succeeded · 579s · 9,237 rows
- semantic_refresh · adf · succeeded · 824s · 4,866 rows
- snow_task_mart · snow_task · succeeded · 773s · 5,182 rows
- snow_task_mart · snow_task · succeeded_with_warnings · 273s · 5,003 rows
- snow_task_mart · snow_task · succeeded · 112s · 4,306 rows
- synapse_load · adf · succeeded · 238s · 10,028 rows
- synapse_load · adf · succeeded · 883s · 6,235 rows
- synapse_load · adf · succeeded · 514s · 6,888 rows
- gold_ops_facts · dbx_job · succeeded · 583s · 8,512 rows
- gold_ops_facts · dbx_job · succeeded · 164s · 7,519 rows
- gold_ops_facts · dbx_job · succeeded · 884s · 3,959 rows
- silver_conform · dbx_job · succeeded · 55s · 5,586 rows
- silver_conform · dbx_job · succeeded · 625s · 6,943 rows
- silver_conform · dbx_job · succeeded · 498s · 6,042 rows
- bronze_normalize · dbx_job · succeeded · 107s · 7,611 rows
- bronze_normalize · dbx_job · succeeded · 519s · 1,073 rows
- bronze_normalize · dbx_job · succeeded · 713s · 3,977 rows
- land_s3_raw · glue · succeeded · 605s · 1,027 rows
- land_s3_raw · glue · succeeded_with_warnings · 621s · 2,074 rows
- land_s3_raw · glue · succeeded · 899s · 2,196 rows
Details
- null_invoice_customer pass — fact_invoices · critical
- orphan_crm_account fail — dim_customer · high
- orphan_erp_customer fail — dim_customer · high
- fuzzy_key_confidence fail — bridge_crm_erp_keys · medium
- negative_margin_lines fail — fact_invoices · medium
- stale_backlog_31plus fail — fact_inventory_backlog · high
- duplicate_sku_check pass — dim_product · low
- opp_without_erp_link fail — fact_opportunities · medium
Executive KPIs
Leadership snapshot — revenue, margin, backlog, pipeline, and samples from one reconciled model.
Revenue YTD
$12,729,420
2026 invoice fact (slicer)
↓ 3% vs 2025
Gross margin %
54.8%
Blended (slicer)
↓ 1.3 pts (3 mo vs prior 3)
Open backlog
$4,977,044
Open orders
On-time (open lines)
0%
days late ≤ 0
Pipeline value
$368,361,808
Opportunities
Sample conversion %
31.5%
Samples fact
Revenue & margin % by month Combo
Revenue by channel Donut
Revenue by region & channel Stacked
Top customers
Backlog by aging
What the numbers are saying
Synthetic dataset for the Microsoft Fabric platform demo. Revenue and margin trends compare recent periods in this scenario. The point is leadership-ready, reconciled metrics—not a client report or live cloud tenant.
Uses the OpenAI API on synthetic demo numbers only. Public hosts apply rate limits to protect billing—private walkthroughs available on request.
Sales & margin
Where volume grows, where mix shifts, and which reps carry the book—with margin in view.
Revenue by month — top channels Stacked area
Revenue (adjusted series)
Revenue by category
Sales rep leaderboard
Region performance
Customer performance
Rank, mix, and concentration—who grows revenue while eroding margin?
Customers: revenue vs. margin % Scatter
Customer rank (revenue)
Revenue by customer type
Sample-to-order
Does sampling activity convert into real revenue—and how fast?
Samples shipped by month
Conversion % by collection
Backlog & fulfillment
Where open demand is building and where fulfillment pressure is rising.
Open order value by month
Fill score by category
CRM ↔ ERP
Pipeline stages and weighted forecast—does CRM tell the same story as orders?
Pipeline by stage
Weighted pipeline by month
Trust center
Refresh status, row counts, and quality checks that keep numbers defensible.
Last refresh
Monday, September 28, 2026 3:33:57 AM
Row counts by table
Data quality checks
- Dataset is fully invented (no real companies or personal data).
- Measures follow a star-schema style for realistic drill paths.
- Ask us about mapping these patterns to your own ERP and CRM sources.
- Quality fail · orphan_crm_account: 26 rows (high).
- Quality fail · orphan_erp_customer: 31 rows (high).
- Quality fail · fuzzy_key_confidence: 33 rows (medium).
- Quality fail · negative_margin_lines: 1876 rows (medium).
- Quality fail · stale_backlog_31plus: 3030 rows (high).
- Quality fail · opp_without_erp_link: 1011 rows (medium).
Semantic model
Shared tables and certified measures—the foundation for consistent answers and AI-ready Q&A.
Model tables
- dim_date
- dim_region
- dim_channel
- dim_sales_rep
- dim_customer
- dim_product
- fact_invoices
- fact_sales_orders
- fact_inventory_backlog
- fact_samples
- fact_opportunities
- bridge_crm_erp_keys
- fact_data_quality_events
- fact_pipeline_runs
- dim_semantic_measure
- fact_medallion_stats
- dim_warehouse_object
- demo_scenario
- data_dictionary
Certified measures
- Total Revenue
- Revenue YTD
- Gross Margin
- Gross Margin %
- Order Value
- Open Backlog
- Pipeline Value
- Weighted Pipeline
- Samples Shipped
- Converted Samples
- Sample Conversion %
Example natural language questions
- What is revenue YTD by channel?
- Which customers grew backlog the most?
- Show margin % trend by month.
- Who are the top reps by pipeline value?
- What is the CRM↔ERP match rate?
How to present this