PLATFORM & METHODOLOGY
How We Modernize Enterprise Data Warehouses
A rigorous, architecture‑first methodology built for regulated enterprises — combining deep technical assessment, cloud‑native platform design, and governed pipeline engineering into a structured, fixed‑scope delivery model.
Our modernization platform is not a framework borrowed from another context. It is a delivery methodology built specifically for the environments our clients operate in — healthcare, life sciences, pharma, and financial services — where governance, compliance, and audit readiness are non‑negotiable architectural requirements, not post‑deployment additions.
THE METHODOLOGY
Three Phases. Clear Deliverables. No Ambiguity About What You Are Getting.
Every modernization engagement follows the same structured methodology — calibrated in scope to the complexity and maturity of your environment, but consistent in rigor and transparency at every stage.
01
Technical Assessment & Discovery
We conduct a comprehensive technical audit of your existing data warehouse — architecture, pipelines, data quality, governance posture, lineage coverage, and accumulated technical debt. We stress‑test assumptions, identify the constraints that are actually limiting performance and scalability, and build a complete picture of the current state before any design decisions are made.
What you receive:
• Current‑state architecture documentation and performance analysis
• Technical debt register with risk classification
• Data quality and lineage gap assessment
• Governance posture evaluation against industry requirements
• Platform recommendation with comparative cost modeling
02
Platform Design & Architecture
We design the target‑state architecture — cloud‑native, governed, and built for the specific workloads, compliance requirements, and analytical demands of your organization. Design decisions are made with the full context of the assessment in view. Nothing is templated. Every recommendation is specific to your environment.
What you receive:
• Target‑state architecture blueprint (cloud‑native, Azure‑aligned)
• Pipeline architecture design (ingestion, transformation, semantic layer)
• Governance and lineage framework design
• Compliance and audit readiness architecture
• Implementation sequencing with dependency mapping
03
Phased Implementation & Migration
We execute the modernization in phases — sequenced to deliver value early, manage risk throughout, and maintain full business continuity. Every workload migration is validated before the next phase begins. Production never stops while modernization proceeds.
What you receive:
• Re‑engineered pipelines (ingestion through semantic layer)
• Implemented governance and lineage automation
• Compliance and audit readiness infrastructure
• Power BI executive dashboard (Modernization Sprint and Full Platform engagements)
• Post‑deployment support (90 or 180 days, depending on engagement tier)
• Founder‑led executive briefing at delivery
TECHNICAL ARCHITECTURE
What a Modernized Data Warehouse Actually Looks Like
The target‑state architecture we design and build is not generic cloud migration. It is a governed, cloud‑native data platform — engineered to support analytics, AI, and compliance at enterprise scale.
Cloud‑Native Pipeline Architecture
Modern ingestion and transformation pipelines built on Azure Data Factory, Synapse Pipelines, and Azure Fabric — designed for reliability, observability, and operational efficiency. Bronze‑to‑Silver‑to‑Gold patterns ensure data quality is enforced at every layer, not assumed at the end.
Automated Governance & Lineage
End‑to‑end data lineage implemented at the architecture level — not retrofitted after the fact. Every data asset is traceable from source to consumption, with governance workflows that enforce policy automatically rather than relying on manual compliance processes.
Semantic Layer & KPI Alignment
A structured semantic layer that defines and enforces consistent business logic across reporting, analytics, and AI consumption. Conformed dimensions, verified KPI definitions, and a governed metadata registry ensure that every consumer of the data is working from the same authoritative source.
Compliance & Audit Readiness
Architecture designed to meet the specific compliance requirements of regulated industries — 21 CFR Part 11, GxP, SOX, HIPAA — with audit trails, access controls, and documentation built into the platform from the ground up.
TECHNOLOGY ALIGNMENT
Built on the Platforms Your Organization Already Operates
We do not impose a preferred vendor stack. We design and build within the platforms your organization has already committed to — optimizing for what you have invested in, not what we prefer to work in.
Azure Data Factory & Synapse Pipelines
Enterprise‑grade data orchestration and transformation — configured for your specific workload patterns and compliance requirements.
Azure Fabric
Unified analytics platform integration for organizations adopting Microsoft Fabric as their target‑state analytics environment.
Power BI
Governed semantic layer and executive reporting — connected directly to the modernized data platform with enforced KPI definitions and lineage‑tracked data.
Databricks
Advanced analytics and machine learning workloads — integrated into the governed data architecture for organizations with data science and AI requirements.
Snowflake
Cloud data warehousing for organizations outside the Azure‑native stack — with the same governance, lineage, and compliance architecture applied regardless of platform.
Legacy Platform Migration
Structured migration from Teradata, Netezza, SQL Server, Oracle, and other legacy EDW platforms — with workload validation at every stage.
REGULATED INDUSTRY EXPERTISE
Governance and Compliance Are Not Add‑Ons. They Are Architecture.
Our modernization methodology was built in regulated environments — and it shows in every design decision. We do not treat compliance as a checklist item applied after the architecture is built. We treat it as a constraint that shapes the architecture from the first decision.
What This Means in Practice
Every pipeline we design includes lineage capture from day one. Every governance framework we implement is automated, not manual. Every compliance requirement — 21 CFR Part 11, GxP, SOX, HIPAA — is addressed in the architecture itself, not in a post‑deployment audit response. When your compliance team, your auditors, or your regulators ask how the data got here and what decisions were made along the way, the platform answers that question automatically.
DELIVERY MODEL
Founder‑Led. Fixed‑Scope. No Surprises.
Every engagement at On Point BI is founder‑led — from scoping through delivery. You are not handed off to a junior team after the sale. The same people who assessed your environment and designed your architecture are the ones who build and deliver it.
Fixed Scope, Fixed Price
Every engagement is defined with clear deliverables and a fixed investment before work begins. There are no surprise overages, no scope creep invoices, and no ambiguity about what you are getting.
Weekly Check‑Ins Throughout Delivery
You receive weekly progress updates at every engagement tier — with visibility into what has been built, what is in progress, and what is coming next.
Founder‑Led Executive Briefing at Delivery
Every engagement closes with a founder‑led executive briefing — not a handoff to a junior team, not a recorded walkthrough. The same person who led your engagement walks your leadership through what was built, what decisions were made, and how to extract maximum value from your modernized platform going forward.
READY TO EVALUATE THE FULL ENGAGEMENT?
See Exactly What You Get — and What It Costs
Review the complete pricing breakdown for each engagement tier — with transparent deliverables, clear timelines, and the investment required at each level.