At a Glance (The 7‑Step Method)
From questions to measurable outcomes
We start with the decisions you need to make and work backward to the data and design. Our 7‑step method ensures each phase builds trust, accelerates insight, and sustains adoption.
- Discover & Align — Define goals, decisions, scope, and success criteria.
- Data Foundation — Build a governed Warehouse/Lakehouse across your systems.
- Semantic Layer — Create secure Tabular Models aligned to business domains.
- Metrics & KPI’s — Document and implement decision‑grade definitions in DAX.
- Visualize — Deliver role‑based dashboards and scorecards in Power BI.
- Enable & Govern — Training, standards, and guardrails for safe self‑service.
- Iterate & Scale — Expand coverage, refine KPI’s, and sustain platform health.
KPI‑First, Not Dashboard‑First
Start with the decision, not the chart
Dashboards only help when the metrics are right. We facilitate working sessions to define KPI’s the way your leaders run the business—what they measure, how they calculate it, and what action it drives. We then implement those definitions once in the semantic layer, so every report uses the same logic.
- Clarity: Plain‑language definitions and ownership
- Consistency: Certified KPI’s used across teams
- Confidence: Less debate, more decisions
“Once we aligned on KPI definitions, reporting time dropped dramatically—and meetings got shorter.”
What You’ll See and Get (By Phase)
Deliverables and timeline expectations
Scope determines timing, but here’s what a typical foundational engagement looks like.
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Phase 0 — Discover & Align (1–2 weeks)
- Workshops: goals, decisions, KPI discovery
- Source system inventory & complexity assessment
- Success criteria and roadmap
Deliverables: Discovery summary, draft KPI list, backlog, high‑level architecture
Phase 1 — Data Foundation (3–6 weeks)
- Warehouse/Lakehouse design and build (Fabric, Azure SQL, or SQL Server)
- Pipelines, data quality checks, historization, conformed dimensions
Deliverables: Schema, data dictionary, pipelines, lineage, runbook
Phase 2 — Semantic Layer & KPI’s (3–6 weeks)
- Tabular Models with RLS, roles, and performance tuning
- KPI implementation in DAX with documentation and testing
Deliverables: Model(s), KPI catalog (business + technical), test cases
Phase 3 — Visualize, Enable & Govern (2–4 weeks)
- Power BI report suites and executive scorecards
- Governance playbook, deployment pipelines, training
Deliverables: Dashboards, standards, training materials, admin procedures
Single source of truth • Decision‑grade KPI’s • Dashboards people use
Governance Woven In
Enablement without chaos
We make self‑service safe. Governance is not optional; it’s built into our approach from day one.
- Security: RLS, role design, PII handling, and least‑privilege access
- Workspaces & Pipelines: Dev/Test/Prod with CI/CD discipline
- Certification: Metric and dataset certification with ownership and lineage
- Standards: Naming conventions, UX patterns, performance guidelines
- Operations: Admin runbook, monitoring, and change management
Training & Adoption
Your team, enabled
We upskill your people so your investment scales.
- Executives & Leaders: Reading KPI’s, drill‑downs, and action‑taking
- Consumers: Navigating dashboards and asking better questions
- Creators: Power BI design, DAX patterns, and model usage
- Admins: Workspace strategy, pipelines, and platform operations
Office hours, recorded sessions, and a living documentation hub
Platform Choices (Microsoft‑Only, Fit‑for‑Purpose)
Fabric, Azure, or SQL Server—designed for your reality
We upskill your people so your investment scales.
We recommend the least complex stack that achieves your goals and roadmap. We work across:
- Microsoft Fabric (Lakehouse/Warehouse) for modern, unified analytics
- Azure SQL for cloud‑hosted relational foundations
- SQL Server for efficient on‑premises or hybrid needs
Front door: Power BI for visualization, scorecards, and distribution
Sample Two‑Week Kickoff Plan
What the first 10 business days look like
Week 1:
- Day 1–2: Discovery workshops, KPI inventory, environment readiness
- Day 3–4: Architecture finalization, source access, modeling standards
- Day 5: First pipelines and data quality checks
Week 2:
- Day 6–7: Initial Tabular Model with RLS and a pilot KPI implemented
- Day 8: First insights prototype in Power BI
- Day 9: Review, backlog grooming, next KPI wave
- Day 10: Governance setup draft, training plan, and milestone readout
How We Measure Success
Outcomes we commit to
Metrics we track with you:
- Time‑to‑Insight: Days to minutes for recurring questions
- Adoption: Monthly active users and executive engagement
- Trust: Reduction in conflicting definitions and ad‑hoc spreadsheets
- Performance: Model refresh and report rendering times
- Security: Audit‑ready lineage and access controls