Financial Data Engineering

Chapter 11. Financial Data Workflows

Throughout this part of the book, you have explored the fundamental layers of the financial data engineering lifecycle: ingestion, storage, transformation and delivery, and monitoring. Adhering to this structured framework is crucial for building and maintaining efficient financial data infrastructures.

Importantly, as your company expands, the financial data infrastructure will become larger and more complex, generating many interdependencies and links between the different layers. To address this challenge, further refinement is required to build multiple independent and specialized data processing components. Data engineers call these components data pipelines or workflows.

This chapter will explore the foundational concepts of data workflows, introducing the ideas of workflow-oriented software architectures and workflow management systems. Then, it will cover the main types and characteristics of financial data workflows that can be implemented to handle financial data processing tasks.

Workflow-Oriented Software Architectures

Before explaining workflows, it’s important to understand the business rationale behind their practicality. First, as a natural part of the growth journey of any digital company, the technological stack tends to increase in size and complexity, creating numerous interdependencies, logical flows, and interactions among various system components. For this reason, the software development community has identified the ...