Financial Data Warehousing & Lakehouse Architecture: Designing Scalable SQL-First Systems for Trading, FP&A, Risk, and Real-Time Analytics

Name: Financial Data Warehousing & Lakehouse Architecture: Designing Scalable SQL-First Systems for Trading, FP&A, Risk, and Real-Time Analytics
Brand: Independently Published
SKU: 9798278766254
Price: 3587.0 INR
Availability: InStock

by Alice Schwartz , William Crestford

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ISBN13: 9798278766254
Binding: Paperback
Subject: N/A
Publisher: Independently Published
Publisher Imprint: Independently Published
Publication Date: December 14, 2025
Pages: 576
Original Price: GBP 31.4
Language: English
Edition: N/A
Item Weight: 762 grams
BISAC Subject(s): Languages / General

About The Book

Reactive Publishing

Financial organizations do not suffer from a lack of data. They suffer from fragmented systems, inconsistent definitions, and architectures that fail under scale.

Financial Data Warehousing & Lakehouse Architecture is a practical guide to designing SQL-first financial data platforms that remain coherent, auditable, and performant as complexity increases. It bridges the gap between classical data warehousing theory and modern lakehouse implementations, translating both into financial systems that support decision-making, risk management, and real-time analytics.

This book is written for professionals responsible for building and maintaining the data backbone of financial organizations. It focuses on architectural decisions that determine whether financial data becomes a strategic asset or a long-term liability.

What this book covers

Core principles of financial data warehousing
Star, snowflake, and hybrid schemas for financial use cases
Designing fact and dimension tables for markets, accounting, and planning
Lakehouse architectures and their role in modern finance stacks
Batch vs near-real-time pipelines for financial reporting and analytics
Establishing a single source of truth across FP&A, risk, and trading
Data governance, lineage, and auditability in financial systems
Cost, performance, and scalability tradeoffs in large financial platforms

The book emphasizes engine-agnostic design, allowing readers to apply the concepts across Snowflake, BigQuery, Redshift, Delta Lake, Iceberg, and other modern data platforms without locking into vendor-specific implementations.

Who this book is for

Data architects and analytics engineers
Finance and FP&A leaders designing enterprise reporting systems
Trading and risk infrastructure professionals
Senior analysts moving beyond spreadsheet-based workflows
Engineering managers responsible for financial data platforms

This book assumes familiarity with SQL and financial data concepts. It is intended for readers who already understand how to query data and now need to understand how to design systems that scale, remain trustworthy, and support high-stakes financial decisions.

Financial Data Warehousing & Lakehouse Architecture provides a structured framework for building financial data platforms that are resilient, transparent, and capable of supporting both historical analysis and real-time operational insight.

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