Architecture First Approach

Fix BI at the
Architecture Level,
Not the Dashboard Level

Define models, metrics, and security once, then let every report reuse them. Stop building tech debt.

System Architecture v2.0
STATUS: OPTIMIZED
Raw
Source
ingest_stream
Core
Semantic Model
Governance Enforced
RLS Policy Active
BI
Net Revenue
$2.4M
12%
System Healthy
Latency: 24ms

When BI Grows Faster Than the Architecture

Most BI problems are architecture problems in disguise. Without a plan, you get chaos.

Finance vs. Ops Disconnect

Finance, sales, and operations report different numbers for “revenue” or “margin.” Reviews start with reconciliation.

Logic Divergence

Dashboards query source systems directly. Logic diverges by analyst, tool, and quarter.

Security Bottlenecks

No clear rules exist for who can see what. Risk and audit concerns slow down access to data.

The Usual Chaos

Uncontrolled Direct Connections

The Architecture Fix

Raw Data
Semantic Layer (Governed)

The Architecture Dividend

Result: high BI spend, slow decisions, and limited trust in the numbers... Fixed at the foundation.

40%
Faster Reporting
0
Metric Disputes
100%
Audit Traceability
$$$
Predictable Cost
Capabilities

Core Capabilities in BI Architecture

STRATEGY MAP
Corporate Objective
Increase EBITDA by 15%
Sales Domain
CAC & LTV
Ops Domain
Supply Chain Cost
Required Data Product
Executive Profitability Dashboard
01

BI Strategy & Target Architecture

Design BI as an operating layer, not a tool roll-out.

Decision & KPI Mapping

Map executive, functional, and operational decisions to the data they require. Prioritize domains by P&L impact.

Platform Alignment

Align existing tools (Power BI, Looker, Tableau) to a common pattern. Identify where current usage breaks governance.

02

Semantic Modeling & Metric Layer

Create one place where numbers are defined and enforced.

Domain Data Models

Design fact and dimension models for revenue, margin, churn. Implement conformed dimensions for customers and products.

History Handling (SCD)

Implement SCD patterns where required. Ensure historical views remain consistent when master data changes.

Old Way (Ad-hoc SQL)
New Way (Semantic)
SELECT sum(amt)
FROM raw_sales
WHERE status != 'fail'
// Logic buried in SQL
// Copied 50 times
select *
from metrics.revenue
where region = 'NA'

// Logic defined centrally
// Reused everywhere
RLS Policies
ACTIVE
Role Region Access PII Visibility
Admin ALL Show
EU Manager EU_ONLY Masked
Analyst ASSIGNED Masked
03

Data Access & Security

Control who sees what, at acceptable speed and cost.

Security Model & RLS

Define row-level security by role, region, and BU. Align BI access with IAM.

Performance & Cost

Model expected query load. Configure BI and warehouse settings to keep cost per report within bounds.

04

Self-Service & Governance

Enable controlled self-service instead of uncontrolled sprawl.

Curated Data Sets

Publish governed data sets with clear joins, metrics, and row-level security applied. Limit direct access to raw tables.

Content Lifecycle

Define standards for creation, promotion, and archiving of dashboards. Introduce certification for official content.

Analyst Workbench
fct_sales_gold
Updated: 2h ago • Owner: Finance
CERTIFIED
sandbox_marketing_v2
Updated: 2d ago • Owner: J. Doe
EXPERIMENTAL
Job: weekly_board_pack
08:00
Data Refresh
Semantic Layer Update
08:15
PDF Generation
Rendered via Headless Browser
08:20
Distribution
Slack #exec-team & Email
05

Reporting & MIS Integration

Make detailed reporting run on the same architecture as dashboards.

MIS & Management Reporting

Align recurring MIS packs with the same semantic models as BI. Parameterize views for BU, region, and product lines.

Distribution & Scheduling

Architect refresh and delivery patterns for daily/weekly reporting. Integrate with email, portals, and embedded analytics.

The Reference Architecture

1

Ingest & Store

Snowflake, BigQuery, Redshift, Databricks
Raw Data Lake
Transformation
2

Modeling Layer

dbt, SQLMesh, Coalesce
Curated Models
3

Semantic Layer

Cube, dbt Semantic, LookerML
Defined Metrics
4

Consumption

Power BI, Tableau, Notebooks
Governed Insights

Problem → Architecture Fix → Result

Executive Reporting

Problem: Different versions of revenue and margin appear across decks. Close cycles drag.

Fix: Unified semantic layer; executive workspace anchored on certified KPIs.

Clean, defensible numbers.
Multi-Region Reporting

Problem: Regions maintain their own logic. Group consolidation is painful.

Fix: Shared conformed dimensions and core KPIs; local extensions layered on top.

Faster group reporting.
Audit-Sensitive Envs

Problem: Audit trails are weak. Risk and finance push back on data trust.

Fix: Metric catalog, tested models, and lineage from dashboard to source.

Stronger audit posture.

Maturity Evolution

Phase 1 – Audit and Stabilize

Inventory tools, dashboards, and data sources. Identify conflicting metrics and high-risk reports.

Month 1-2
Month 3-6

Phase 2 – Architect and Rebuild

Design target BI architecture and semantic layer. Rebuild high-impact domains (finance, sales) on the new foundation.

Phase 3 – Scale and Govern

Onboard additional domains. Tighten performance, governance, and self-service patterns.

Month 6+

Commercial Certainty Pledge

If leadership expects BI to stand up under board questions and audits, architecture cannot remain implicit.

Architect on top of governed data
Embed testing & lineage
Tie decisions to cost & risk
Design for SME realities