Apache Kylin Training is a practical, hands-on program designed to equip learners with the skills required to build and manage OLAP (Online Analytical Processing) cubes for large-scale big data analytics. This training focuses on Kylin architecture, cube design, data modeling, query optimization, and integration with Hadoop ecosystem components such as Hive, HDFS, and Spark. Participants will gain real-world experience in enabling ultra-fast analytical queries on massive datasets using pre-computation techniques and distributed processing.

Participants will gain strong practical skills in Apache Kylin, enabling them to build high-performance OLAP solutions for big data analytics and enterprise reporting systems.

• Data Engineers and BI Developers
• Data Warehouse Professionals
• Big Data Analysts and Architects
• Hadoop Developers and Administrators
• IT Professionals working on analytics platforms

• Basic understanding of SQL and relational databases
• Familiarity with Hadoop ecosystem concepts (Hive, HDFS basics)
• Basic knowledge of data warehousing concepts
• Analytical thinking and data interpretation skills

• Apache Kylin architecture and OLAP cube concepts
• Cube design and dimensional modeling
• Data ingestion from Hadoop and Hive sources
• Query optimization and performance tuning
• Pre-computation techniques for large-scale analytics
• Integration with BI tools and SQL interfaces
• Managing and monitoring Kylin environments

Upon completion of this training, participants will be able to design and implement OLAP cubes using Apache Kylin for fast analytical querying. They will be capable of optimizing big data analytics workloads and enabling high-performance reporting on large-scale datasets.

Introduction to Apache Kylin and OLAP Concepts
• Overview of OLAP and big data analytics
• Apache Kylin architecture and components
• Cube fundamentals and star schema concepts
• Setting up Kylin environment

Data Modeling and Cube Design
• Dimensional modeling for OLAP cubes
• Fact and dimension table design
• Cube creation and configuration
• Data source integration (Hive/HDFS)
Query Processing and Optimization
• How Kylin accelerates SQL queries
• Indexing and pre-computation strategies
• Query optimization techniques
• Performance tuning for large datasets

Integration and Advanced Features
• Integration with BI tools and dashboards
• Cube maintenance and monitoring
• Handling large-scale distributed data
• Best practices for production environments

• Kylin architecture and OLAP fundamentals
• Cube design and dimensional modeling
• Data ingestion and integration
• Query optimization and performance tuning
• Pre-computation techniques
• BI integration and reporting

• Hands-on cube creation exercises
• SQL query optimization tasks
• Practical data modeling assignments
• Mini project on OLAP cube implementation

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants who successfully complete the training will receive an AcadNXT Certification in Apache Kylin Training, validating their expertise in OLAP cube design, big data analytics, query optimization, and enterprise BI acceleration using Apache Kylin.