The Data Formats for Data Engineering & Analytics assessment is designed to evaluate a participant’s understanding of the most widely used data formats in modern data platforms and analytics systems.

In today’s data-driven environments, data engineers, analysts, and data professionals frequently work with a variety of data formats across data pipelines, data lakes, cloud platforms, and analytical tools. A solid understanding of how these formats store, structure, and optimize data is essential for building efficient and scalable data systems.

This assessment measures your knowledge of structured, semi-structured, columnar, and serialized data formats commonly used across the data engineering ecosystem.

Participants will answer a set of carefully designed questions that test their conceptual understanding and practical awareness of how different data formats are used within real-world data pipelines, big data platforms, and modern lakehouse architectures.

Key Topics Covered

• JSON (JavaScript Object Notation) for semi-structured data and APIs

• CSV (Comma-Separated Values) for tabular data exchange

• XML (Extensible Markup Language) used in enterprise data systems

• Apache Parquet columnar format used in big data analytics

• ORC (Optimized Row Columnar) high-performance analytics format

• Avro (Apache Avro) schema-based data serialization format

• Protocol Buffers (Protobuf) efficient binary serialization format

• Delta Lake transactional data lake table format

• Apache Iceberg modern data lake table format with versioning

• Apache Hudi incremental data processing and real-time data lake format

Certification Outcome

Upon successfully completing the assessment, participants will receive official recognition from Edvane for demonstrating their knowledge of modern data formats used in data engineering and analytics workflows.

This recognition highlights an individual’s understanding of how different data formats are used to store, process, and exchange data across modern data platforms.