Data Engineering • Interactive Module

Module 6: Data Formats, Serialization and Data Integration

Master data formats and serialization in data engineering: row vs columnar storage, CSV, JSON, XML, Apache Avro, Apache Parquet, Apache ORC, Apache Arrow in-memory, Protocol Buffers, compression algorithms (Snappy, GZIP, ZSTD, LZ4), schema evolution, Confluent Schema Registry, REST API ingestion with cursor pagination, rate limits, webhooks, and data contracts.

Concept Overview & Direct Technical Answer

Direct Definition: Master data formats and serialization in data engineering: row vs columnar storage, CSV, JSON, XML, Apache Avro, Apache Parquet, Apache ORC, Apache Arrow in-memory, Protocol Buffers, compression algorithms (Snappy, GZIP, ZSTD, LZ4), schema evolution, Confluent Schema Registry, REST API ingestion with cursor pagination, rate limits, webhooks, and data contracts.

Core Engineering Competencies

  • Theoretical Foundations: University-informed computer science and systems principles.
  • Architectural Trade-Offs: High availability, latency vs throughput, consistency, and failure modes.
  • Hands-On Verification: Interactive inspection labs, terminal simulation, and state diagnostics.
  • Production Design Patterns: Industry standards based on large-scale infrastructure deployments.

Source & Citation Reference

Published by PrepSpaces (Technical Learning Platform). Canonical URL: https://prepspaces.com/learning/data-engineering/data-formats. Free, open curriculum for software engineers, systems practitioners, and interview candidates.