Description
Book SynopsisPart I: Data Lakehouses, Iceberg, Batch ETL, and Orchestration.- Chapter 1: Foundational Data Engineering Concepts.- Chapter 2: Building a Data Lakehouse with Apache Iceberg.- Chapter 3: Batch ETL Pipeline with Apache Spark.- Chapter 4: Data Visualization with Apache Superset.- Chapter 5: Workflow Orchestration with Apache Airflow.- Part II: Streaming Data and Real-time Analytics. - Chapter 6: Change Data Capture with Debezium and Kafka.- Chapter 7: Low-latency Analytics Dashboard with ClickHouse.- Chapter 8: Real-time Fraud Detection with Apache Flink.- Part III: Machine Learning and Generative AI.- Chapter 9: Building a Product Recommendation Engine with Spark MLlib.- Chapter 10: Vector Similarity Search with Postgres and pgvector.
