Modern data platforms use many different data formats to store, exchange, and process information across systems. These formats are the foundation of data engineering pipelines, analytics platforms, distributed systems, and artificial intelligence applications.
This course provides a clear and practical overview of the most important data formats used in modern data platforms. Instead of focusing on programming implementation, this course explains what these formats are, why they exist, where they are used, and how they are typically processed in real-world data systems. You will learn about structured and tabular data formats such as CSV (Comma Separated Values), TSV (Tab Separated Values), and spreadsheet formats commonly used for storing and sharing structured datasets.
The course also introduces widely used data serialization formats such as JSON (JavaScript Object Notation), XML (Extensible Markup Language), Apache Avro, Protocol Buffers, BSON, and MessagePack that are commonly used in APIs, distributed systems, and streaming platforms. Next, we explore big data storage formats including Apache Parquet, Apache ORC, Apache CarbonData, Apache Arrow, Feather, and HDF5, which are designed for efficient analytics and large-scale data processing in modern big data environments.
You will also learn about modern data lake table formats such as Delta Lake, Apache Iceberg, Apache Hudi, and Apache Paimon that enable reliable data management in modern lakehouse architectures. In addition, the course introduces media formats, graph and knowledge graph formats, and vector embedding formats used in artificial intelligence systems and machine learning applications.
Throughout the course, you will understand where each format is used and how common tools such as Python, data processing frameworks, and analytics systems interact with these formats in real-world data platforms. By the end of this course, you will have a strong conceptual understanding of the major data formats used in modern data engineering, big data analytics, and artificial intelligence ecosystems.
