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Data Engineering 101: Key Principles for Architecting Databases
Building a Strong Foundation for Scalable, Efficient, and Secure Data Systems
Data is at the heart of modern applications, powering everything from e-commerce platforms to machine learning models. Designing a robust database architecture is a critical task that determines the efficiency, scalability, and maintainability of your application. In this article, we’ll explore the foundational principles of data engineering to help you build a database that stands the test of time.
Understanding Application Requirements
The first step in database architecture is understanding the application’s requirements. Ask yourself the following questions:
What is the purpose of the database? Clearly define the business problems the database is meant to solve.
What types of data will you store? Structured, semi-structured, or unstructured data?
What is the workload profile? Is the application read-heavy, write-heavy, or balanced?
A thorough understanding of these requirements will guide the selection of the database type and design approach.
