Platform demo · Databricks lakehouse
Medallion navigator: bronze → silver → gold → semantic
Explore medallion row counts, quality gates, and job stages that land in a semantic model Power BI can trust. Synthetic manufacturer/distributor facts only.
How this maps to Databricks
Databricks consulting with BI handoff (certified practitioner delivery).
- Bronze/silver/gold row counts with certified gold flags
- Databricks job stages from pipeline runs
- Gold → semantic contract panel
- Credential claim is separate; this demo is synthetic data
Related consulting page → · All platform demos · Book My BI Diagnostic
Databricks medallion navigator
Bronze → silver → gold row counts, quality gates, and job stages.
Silver rows
Gold rows
Gold tables are the BI contract after Spark jobs. Certified flags are synthetic.
Lens chart A
Lens chart B
Pipeline / job stages
- 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
Details
- fact_invoices certified — gold · updated 20261231
- fact_sales_orders certified — gold · updated 20261231
- fact_opportunities certified — gold · updated 20261231
- fact_samples certified — gold · updated 20261231
- fact_inventory_backlog certified — gold · updated 20261231
- dim_customer certified — gold · updated 20261231
- dim_product certified — gold · updated 20261231
Executive KPIs
Leadership snapshot — revenue, margin, backlog, pipeline, and samples from one reconciled model.
Revenue YTD
Gross margin %
Open backlog
On-time (open lines)
Pipeline value
Sample conversion %
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 Databricks 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 3:32:23 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