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Build a Cost-Effective Data Warehouse to Unify Your Disparate Financial Systems

Your critical financial data is trapped in disconnected legacy systems—core banking, trading platforms, CRMs. Aggregating this data for regulatory reporting is a manual, error-prone nightmare, leading to delays, inaccuracies, and compliance risks. You need a single source of truth, but enterprise solutions are prohibitively expensive.

This playbook details how to build a powerful, low-cost data warehouse using a fully open-source stack. We leverage Apache Airflow to automate the complex orchestration of data pipelines from your various systems. A self-hosted PostgreSQL database serves as the robust, centralized repository—your single source of truth. This approach eliminates software licensing fees, giving you full control over your data infrastructure, though it requires dedicated DevOps and management resources.

Expected Outcomes

  • Establish a single source of truth for all critical financial data.
  • Automate complex data aggregation and normalization tasks.
  • Drastically reduce errors and delays in regulatory reporting.
  • Eliminate expensive software licensing fees from proprietary vendors.
  • Empower business teams with self-service analytics and reporting.
  • Gain full ownership and control over your data infrastructure.

Core Tools in This Stack

Apache Airflow

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An open-source platform to programmatically author, schedule, and monitor data workflows. Airflow uses Python to create Directed Acyclic Graphs (DAGs) of tasks, providing a dynamic, extensible, and scalable solution for managing complex data pipelines.

Key Features
  • Workflows as Code (DAGs)
  • Rich Web UI
  • Extensible & Pluggable
  • Dynamic Pipeline Generation
  • Scalable Architecture
  • Robust Scheduling
Ideal For

Company Size: Medium, Large

Industries: Technology & Software, Business & Professional Services, Retail & E-commerce, Creative & Media, Health & Wellness

Pricing

Model: Open Source

Tier: Free (Self-Hosted)

Ease of Use

Moderate

PostgreSQL

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PostgreSQL is a powerful, open source object-relational database system with over 35 years of active development that has earned it a strong reputation for reliability, feature robustness, and performance.

Key Features
  • ACID compliance for transactional reliability
  • Highly extensible, allowing user-defined data types, functions, and operators
  • Advanced data types including JSON/JSONB, XML, arrays, and geometric types
  • Multi-Version Concurrency Control (MVCC) for high concurrency
  • Built-in streaming replication for high availability and read scaling
  • Strong conformance to the SQL standard
  • Full-text search capabilities
  • Cross-platform compatibility (Linux, macOS, Windows, BSD, Solaris)
Ideal For

Company Size: Micro, Small, Medium, Large

Industries: Technology & Software, Business & Professional Services, Retail & E-commerce, Creative & Media, Education & Non-Profit, Health & Wellness, Other

Pricing

Model: Open Source

Tier: Free

Ease of Use

Medium

Metabase

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Metabase is an open-source business intelligence tool that enables everyone in a company to ask questions, learn from data, and create visualizations and dashboards, with or without using SQL.

Key Features
  • Graphical Query Builder
  • Interactive Dashboards
  • Native SQL Editor
  • Data Alerts and Subscriptions
  • Broad Database Support
  • Embedding and White Labeling
  • Open Source & Self-Hosting
  • Permissions and Data Sandboxing
Ideal For

Company Size: Micro, Small, Medium, Large

Industries: Technology & Software, Business & Professional Services, Retail & E-commerce, Creative & Media, Education & Non-Profit, Health & Wellness, Other

Pricing

Model: Open Source, Freemium, Subscription

Tier: Mid-Range

Ease of Use

Easy

The Workflow

graph TD subgraph "Open-Source Data Warehouse Stack" direction LR N0["Apache Airflow"] N1["PostgreSQL"] N2["Metabase"] N0 -- "Loads transformed data" --> N1 N1 -- "Serves data for BI" --> N2 end classDef blue fill:#3498db,stroke:#2980b9,stroke-width:2px,color:#fff; classDef green fill:#2ecc71,stroke:#27ae60,stroke-width:2px,color:#fff; classDef orange fill:#f39c12,stroke:#d35400,stroke-width:2px,color:#fff; class N0 blue; class N1 blue; class N2 blue;

Integration Logic

  • CoreSystem DataLink

    This integration establishes a classic ETL (Extract, Transform, Load) pipeline. An Apache Airflow DAG (Directed Acyclic Graph) is scheduled to run at regular intervals. The DAG executes a Python script that extracts data from a source (e.g., a REST API), transforms the data into a structured format using libraries like Pandas, and then loads the cleaned data into a predefined table in a PostgreSQL database. Metabase is connected directly to this PostgreSQL database, allowing it to query the data in real-time and provide up-to-date visualizations and dashboards for business intelligence.

Get Your Financial Data Unification Blueprint

Build a single source of truth to eliminate reporting errors and compliance risks—without the enterprise price tag.