Case Study — AtlasIQ

Financial Analytics Dashboard

Building a Real-Time Financial Intelligence Layer for a 14-Subsidiary Enterprise

Unified multi-entity financial analytics replacing 14 separate Excel workflows

Industry

Enterprise Finance

Timeline

12 weeks

Team

5 engineers

Tech

PostgreSQL + dbt + React

The Challenge

A multi-entity enterprise with 14 subsidiaries had finance teams running separate Excel-based reporting stacks. Monthly consolidation took 3 days, involved 22 manual steps, and produced results immediately questioned by stakeholders due to inconsistent accounting treatments across entities.

Our Approach

How We Solved It

Unified Financial Data Model

Designed a canonical chart of accounts that normalized 14 different entity schemas into a single GAAP-compliant data model without forcing entities to change their local systems.

Automated Reconciliation Engine

Built dbt-powered transformation pipelines that auto-reconcile intercompany eliminations, currency translations, and allocation logic on every data refresh.

Variance Analysis Automation

Replaced manual variance commentary with AI-generated narrative that identifies the top 5 drivers of month-over-month changes across P&L, balance sheet, and cash flow.

Real-Time Drill-Down Dashboards

Delivered a React dashboard with full drill-down from consolidated group P&L to individual transaction level in under 200ms, live-updating as entities post data.

Engineering Process

How We Built It

Incremental dbt Models

Used incremental dbt materialization strategies to process only changed records on each run, reducing full-refresh time from 4 hours to under 8 minutes.

Entity-Level Permission Model

RBAC configuration ensures subsidiary controllers see only their entity's underlying data while group finance has full consolidated visibility.

Audit Trail Architecture

Every transformation is lineage-tracked through dbt's DAG, giving auditors a complete, reproducible path from source system to reported figure.

Architecture Decisions

Key Technical Choices

dbt Over Stored Procedures

Chose dbt transformations over database stored procedures for version control, testing, and documentation — critical for audit readiness at the entity level.

Semantic Layer for Metric Consistency

Implemented a dbt semantic layer so 'revenue' means exactly the same thing across every dashboard, report, and ad-hoc query.

Snapshot Tables for Point-in-Time Reporting

dbt snapshot tables capture daily balance states, enabling accurate historical comparisons and regulatory reporting without relying on system timestamps.

Results

What We Delivered

97%

Reduction in Consolidation Time

Entities Unified

4 hrs

Month-End Close (was 3 days)

100%

Audit Trail Coverage

Solution Blueprint

How It All Fits Together

Ingestion Layer

14 ERP connectors
CDC replication
Schema normalization

Transformation Layer

dbt semantic models
Intercompany elimination
Currency translation engine

Presentation Layer

Executive P&L dashboard
Drill-down explorer
AI variance narrative

Lessons Learned

What We Improved

Agree on the Canonical Model First

Two weeks of finance stakeholder alignment on the unified chart of accounts saved us from a rewrite at week 8. Semantic disagreements are harder to fix than code.

Incremental Builds From Day One

Designing for incremental processing from the start meant we never had to refactor the pipeline when data volumes grew 4x during the project.

Show Value in Week 4

We delivered the first consolidated P&L view at week 4 with just 3 entities. That early win maintained executive sponsorship through the harder integration work.

Related Case Studies

Enterprise SaaS / Finance

Revenue Intelligence Platform

Predictive revenue analytics for a $200M ARR SaaS business

View Case Study

Enterprise / SaaS

Executive Reporting Platform

From static PDF decks to real-time C-suite intelligence in 10 weeks

View Case Study

E-Commerce / Consumer

Customer Insights Engine

Real-time behavioral analytics and personalization for high-volume e-commerce

View Case Study

Related Research

Research Reports for This Industry

View all research →

Enterprise AI24 min

Enterprise AI Adoption Trends 2026

Enterprise AI has crossed the operational threshold. Seventy-two percent of Fortune 500 organizations now run at least one AI system in production — and the average enterprise manages 3.4 concurrent AI initiatives. This report maps the state of enterprise AI across healthcare, manufacturing, financial services, retail, and beyond.

Read report

SaaS Engineering19 min

SaaS Development Benchmarks 2026

What does it actually cost to build and scale a SaaS product in 2026? This report benchmarks engineering team size, deployment frequency, infrastructure spend, and time-to-market across 521 SaaS companies — from $1M ARR seed-stage startups to $100M+ enterprise SaaS leaders.

Read report

AI Agents21 min

AI Agent Adoption Report 2026

AI agents are the most transformative enterprise technology category of the 2025–2026 cycle. This dedicated report examines architecture patterns, deployment economics, governance approaches, and the emerging multi-agent production landscape across 634 organizations — the most comprehensive agent-specific enterprise research available.

Read report

Cloud18 min

Enterprise Cloud Cost Benchmark Report 2026

Enterprise cloud spend reached $780 billion globally in 2025 — yet 32% remains unoptimised waste according to our benchmark data. This report quantifies cloud cost maturity across AWS, Azure, and GCP, mapping FinOps practice adoption, reserved capacity utilisation, and savings plan optimisation against peer benchmarks.

Read report

View all research →

Pricing Intelligence