Data lake and data pipeline design focus on storing large volumes of raw data in centralized repositories and building pipelines to collect, process, and transform data for analytics and machine learning.
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Assess your understanding of data modeling concepts and schema design strategies for analytical databases. This quiz covers dimensional modeling, normalization, denormalization, star and snowflake schemas, surrogate keys, and best practices essential for analytical data environments.
Explore the essentials of data lakes with questions on schema-on-read, storage strategies, scalability, and real-world use cases. This quiz is designed for learners who want to understand how data lakes differ from data warehouses and prepare for interviews or modern data engineering roles.
Test your understanding of data modeling and schema design principles for data lakes. This quiz covers essential concepts such as schema types, data consistency, normalization, partitioning, and best practices for designing scalable and efficient data lake architectures.
Test your understanding of HTTP/REST ingestion design principles, including idempotency, pagination strategies, retry mechanisms, and status codes. This quiz is perfect for anyone wanting to sharpen their skills in designing and consuming reliable APIs using REST.
Test your knowledge of SQL joins, aggregations, deduplication, rollups, and upserts. This quiz helps you review important SQL concepts for building effective pipeline transforms and data workflows.