Transforming Data Requirements into Scalable Architecture

Feb 22

2 min read

I recently completed the DeepLearning.ai Data Engineering Professional Certificate, and one topic that stood out to me was the importance of gathering proper requirements. This process isn't unique to data engineering—it's also crucial in product development and management. While the approach may vary depending on the application, in data engineering, it covers everything from gathering requirements to implementing data systems. In this post, I’ll share a framework I learned that you can apply to any project.

Identify business goals & stakeholder needs

Identify the business goals & stakeholders you will serve
Explore existing systems and stakeholder needs
Ask stakeholders what actions they will take with the data product

In this stage, your goal is to understand the business objectives and stakeholder needs driving the project. Start by clarifying the company's high-level goals. Then, identify the stakeholders, their needs, and how these align with the business goals. Engage with stakeholders to understand existing systems, their limitations, and additional needs. Also, ask how they plan to use the data products, which will help define the system’s functional requirements.

Define system requirements

Translate stakeholder needs to functional requirements
Define non-functional requirements
Document and confirm requirements with stakeholders

In the second stage, your goal is to define the functional and non-functional requirements. Functional requirements describe what the system must do to meet stakeholder needs, while non-functional requirements outline the technical specifications. Once these are defined, document them and confirm with stakeholders that the proposed system will fulfill their needs.

Choose tools & technologies

Identify tools & technologies to meet non-functional requirements
Perform a cost-benefit analysis and choose between comparable tools and technologies
Prototype and test your system, and align it with stakeholder needs

In the third stage, you'll select the tools and technologies for your system. Start by identifying options that meet the requirements, then evaluate trade-offs using a cost-benefit analysis. Consider factors like licensing fees, cloud resource costs, and other expenses for building and maintaining the system.

Build, evaluate, iterate & evolve

Build & deploy your production data system
Monitor, evaluate, and iterate on your system to improve it
Evolve your system based on stakeholder needs

After selecting the best tools, create a prototype to test if it meets expectations and delivers value. Get stakeholder feedback, iterate as needed, and ensure it will succeed in production. Finally, build and deploy the system, then monitor and improve its performance, adapting to changing needs or new tools.

Example use case

About

Benjamin ("Benj") Tabares Jr. is an experienced data practitioner with a strong track record of successfully delivering short- and long-term projects in data engineering, business intelligence, and machine learning. Passionate about solving complex customer challenges, Benj leverages data and technology to create impactful solutions. He collaborates closely with clients and stakeholders to deliver scalable data solutions that unlock business value and drive meaningful insights from data.