DENG 251 Building an Open Data Lakehouse Using Apache Iceberg
- Duration: 32 hours
- Exam Voucher: Yes
- Language: English
- Course Delivery : E - Learning Access
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Course Overview
The DENG-251: Building an Open Data Lakehouse Using Apache Iceberg course is designed to provide data engineers, architects, and analytics professionals with the skills needed to build and manage an open data lakehouse architecture leveraging Apache Iceberg. This course focuses on the core principles and best practices for implementing scalable, performant, and governable data lakehouse solutions that unify data warehousing and data lake capabilities. Participants will gain hands-on experience with Iceberg table formats, metadata management, query optimization, and integration with popular processing engines such as Apache Spark and Hive.
Course Details
- Understand the principles of open data lakehouse architecture
- Hands-on experience with Apache Iceberg table format and metadata handling
- Ability to design and implement performant and scalable data platforms
- Expertise in integrating Iceberg with processing engines like Spark and Hive
- Skills to optimize queries, manage schema evolution, and ensure data governance
- Preparation for real-world data engineering roles using modern lakehouse technologies
- Open to data engineers, data architects, analytics professionals, and IT practitioners
- Ideal for professionals involved in building or scaling data platforms and analytics solutions
- Basic understanding of data processing, SQL, and distributed systems is recommended
- Familiarity with Apache Spark or Hadoop ecosystem components is beneficial
- Corporate sponsorship or group participation is encouraged
- Master the fundamentals of open data lakehouse design and implementation
- Learn how to implement Apache Iceberg table structures and metadata management
- Gain expertise in integrating Iceberg with Spark, Hive, and other processing engines
- Understand schema evolution, partitioning strategies, and performance optimization
- Develop skills in query tuning, data governance, and operational practices
- Achieve readiness to implement modern data lakehouse solutions in enterprise environments
- Introduction to Data Lakehouse Architecture
- Apache Iceberg Fundamentals and Table Format
- Metadata Management and Table Operations
- Integrating Iceberg with Spark & Hive
- Schema Evolution and Partitioning Techniques
- Query Optimization and Performance Tuning
- Data Governance and Compliance Features
- Handling Large-Scale Data Workloads
- Best Practices for Lakehouse Deployment
- Hands-On Labs and Real-World Scenarios
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