data
Practical resources about data for software engineers.
87 results
Understanding Data Processing in Software Engineering
Every application eventually deals with data — parsing user input, serializing objects for APIs, validating form submissions, or transforming records between formats. Getting data handling right is what separates fragile scripts from production-grade systems.
This collection covers practical recipes and patterns for working with JSON, CSV, XML, YAML, and custom formats. You will find copy-paste solutions for common tasks like flattening nested objects, sanitizing user input, generating slugs, and formatting dates across Python, Java, and JavaScript.
Vector Databases — AI/ML Embeddings and Similarity Search
A practical guide to vector databases: embeddings, similarity search, approximate nearest...
A/B Testing: Experimentation Frameworks for Data-Driven
A practical guide to A/B testing: experiment design, statistical significance, sample sizing,...
AWS Basics — Core Services for Developers
A practical guide to AWS core services for developers: compute, storage, databases, networking, and...
Azure Basics — Core Services for Developers
A practical guide to Microsoft Azure core services for developers: compute, storage, databases,...
GCP Basics: Core Services for Developers
A practical guide to Google Cloud Platform core services for developers: compute, storage,...
Terraform Best Practices — Modules, State, and Workspaces
A practical guide to Terraform best practices: module design, remote state management, workspaces,...
GDPR Compliance — A Practical Guide for Developers
A developer-focused guide to GDPR compliance: data subject rights, lawful basis, data minimization,...
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