FREE 30-MINUTE BI DIAGNOSTIC
Reporting your leadership team can finally trust.
For mid-market manufacturers and distributors tired of ERP, CRM, and Excel telling different stories. We find the bottleneck and the first fix—in one working session.
No sales deck. Bring one reporting problem. Leave with concrete next steps.
- 19+ years inside real operating systems
- Power BI, Fabric, warehouses, and semantic models
- Chicago-based · Available remotely
Your reporting problem may be bigger than the dashboard.
Conflicting metrics
Finance, sales, operations, and leadership use different definitions of revenue, margin, pipeline, customers, or performance.
Fragmented platforms
Data is spread across ERP, CRM, cloud applications, warehouses, spreadsheets, and disconnected BI tools.
Fragile delivery
Reports depend on manual exports, individual analysts, undocumented SQL, or pipelines nobody wants to touch.
We connect the architecture, data model, and reporting layer so leadership can trust the answer—regardless of where the data lives.
Built for teams caught between business questions and platform complexity.
Aurea Quantra works with executives, operations leaders, finance teams, IT departments, and internal analysts who need dependable reporting but do not need a massive consulting firm.
- Your Power BI or Tableau dashboards no longer reconcile
- You are evaluating Fabric, Snowflake, Redshift, Databricks, or another warehouse
- Your ERP and CRM tell different stories
- You need to move reporting from on-premises SQL or Excel into the cloud
- Your current warehouse is expensive, slow, or difficult to maintain
- You need a semantic model and KPI definitions before building more dashboards
- You need a practical roadmap across Microsoft and AWS technologies
- You inherited a BI stack with little documentation or governance
Start with one decision your team needs to make.
Free 30-Minute BI and Data Platform Diagnostic
Bring one reporting, architecture, warehouse, integration, or data-quality problem. We’ll identify the likely bottleneck, the best first deliverable, and a realistic next step.
You’ll leave with:
- A practical assessment of the current BI or data-platform problem
- Identification of the highest-risk reporting or architecture gap
- A recommended first dashboard, data-model, pipeline, or platform step
- A realistic phase-one timeline and budget range
- Honest guidance when the existing platform should be improved rather than replaced
From source systems to executive decisions
BI strategy and executive reporting
Define the KPIs, operating questions, and reporting experience leadership actually needs—then build a realistic roadmap to deliver it.
Cloud data warehouses and lakehouses
Design, assess, or modernize the platform beneath your analytics without forcing a one-size-fits-all architecture.
Data integration and semantic modeling
Reconcile ERP, CRM, finance, SaaS, and operational data into governed models that produce consistent answers.
BI modernization and rescue
Stabilize reporting environments that have become slow, expensive, undocumented, or impossible to trust.
Discuss My BI Stack See detailed services →
Platform-aware. Business-first.
The right answer depends on your current systems, internal skills, scale, security requirements, and budget. Aurea Quantra helps clients improve the environment they already have, connect platforms that need to work together, and modernize only where the business case is clear.
Business intelligence
Power BI · Tableau · Excel · Amazon QuickSight · other SQL-compatible BI tools where appropriate
Microsoft data platform
Microsoft Fabric · Azure · OneLake · Data Factory · Synapse environments · SQL Server · Power BI semantic models
AWS analytics
Amazon Redshift · Amazon S3 · AWS Glue · Athena · Amazon QuickSight · Bedrock-related analytics use cases where appropriate
Cloud and lakehouse
Snowflake · Databricks · Apache Spark / PySpark · Delta Lake · Parquet · open table formats where appropriate
Operational systems
ERP · CRM · finance · e-commerce · production and inventory · SaaS applications · APIs, databases, exports, and legacy systems
Disclaimer: Platform names identify technologies we can assess, integrate, or support. They do not imply vendor partnership or certification unless explicitly stated.
Senior-level BI help without the large-consulting-firm overhead.
I’m Paul Rendleman. I’ve spent more than 19 years working across the systems that run an operating business—ERP, CRM, SQL, finance, sales, production, executive reporting, cloud data, and analytics delivery.
Credential: Databricks-certified practitioner
Aurea Quantra brings that operator’s perspective to modern BI work. The platform matters, but the real goal is a maintainable data model, reconciled metrics, and reporting that helps someone make a decision.
You work directly with me from discovery through architecture, delivery, and handoff.
Broad platform capability. Deep operational context.
Aurea Quantra supports BI and data-platform work across mid-market industries, with especially strong alignment where sales, finance, operations, inventory, fulfillment, projects, or customer activity must reconcile.
IDEAL-FIT SCENARIO
Manufacturing and distribution
When it fits: Margin, backlog, inventory, fulfillment, production, customer performance, and pipeline-to-order visibility are argued about every week.
What we deliver: Governed operational models, executive scorecards, and ERP/CRM reconciliation patterns leadership can defend.
IDEAL-FIT SCENARIO
Professional and project services
When it fits: Utilization, project margin, staffing, pipeline, and delivery performance live in separate tools and spreadsheets.
What we deliver: Shared definitions for revenue and margin, project/ops scorecards, and a maintainable model for leadership reviews.
IDEAL-FIT SCENARIO
Multi-location and commerce
When it fits: Location performance, inventory, channel mix, and customer behavior cannot be compared cleanly across sites or brands.
What we deliver: Conformed location/customer dimensions, operational scorecards, and reporting that survives the next expansion.
IDEAL-FIT SCENARIO
Private-equity portfolio reporting
When it fits: Operating partners need standardized KPIs, faster diligence-ready reporting, and practical modernization across portfolio companies.
What we deliver: KPI standards, data-quality assessment, and phased reporting modernization without enterprise-consulting overhead.
IDEAL-FIT SCENARIO
Retail, logistics, and tech-enabled services
When it fits: Mid-market operators need dependable analytics across commerce, logistics, SaaS operations, or hybrid service models—without a massive platform org.
What we deliver: Vendor-neutral roadmap, semantic models, and first trusted dashboards tied to the decisions that matter now.
The kinds of outcomes we build toward
REPRESENTATIVE SCENARIO — FABRIC + POWER BI
Replace conflicting Excel packs with a governed Fabric/Power BI semantic model for executive KPIs, margin, and backlog.
REPRESENTATIVE SCENARIO — AWS + REDSHIFT
Assess or modernize Redshift/S3 analytics so finance and operations share one maintainable warehouse layer.
REPRESENTATIVE SCENARIO — SNOWFLAKE + BI
Connect Snowflake to Tableau or Power BI with clear metric definitions and a practical consumption model.
REPRESENTATIVE SCENARIO — DATABRICKS + POWER BI
Use lakehouse tables and Spark jobs that feed trusted Power BI models, not orphan pipelines.
REPRESENTATIVE SCENARIO — ERP/CRM/SQL
Reconcile ERP and CRM into one semantic layer so pipeline, orders, invoices, and customer history tell the same story.
SYNTHETIC DEMO
Explore a fictional manufacturer/distributor reconciled operational model—executive KPIs, drill paths, and storytelling leadership can defend. Open the operational BI demo →
Stop reconciling the same numbers every week.
Bring the report, architecture, warehouse, or workflow your team does not trust. We’ll map the fastest path to a dependable first result.
Free 30-minute working session · No obligation
Privacy & synthetic data: Public demos use invented businesses and synthetic datasets only. What you share in a BI Diagnostic stays confidential.