Oracle Data Warehouse Concepts

Module 1: Introduction to Data Warehousing

• Data warehouse concepts and history
• OLTP vs. OLAP systems
• Data warehouse architecture: EDW, ODS, data mart
• Oracle data warehousing solutions overview
• Data warehouse use cases and ROI

Module 2: Data Warehouse Design

• Dimensional modeling concepts
• Star schema and snowflake schema
• Fact tables and dimension tables
• Slowly changing dimensions (SCD) types 1, 2, 3
• Data vault modeling introduction

Module 3: Oracle Database for Data Warehousing

• Oracle partitioning for DW
• Partition types: Range, list, hash, composite
• Parallel query execution
• Bitmap indexes for DW
• Materialized views and query rewrite

Module 4: ETL Concepts

• Extract, Transform, Load (ETL) process
• ETL vs. ELT approaches
• Data quality in ETL pipelines
• Change data capture (CDC) methods
• Oracle Data Integrator (ODI) overview

Module 5: Oracle Autonomous Data Warehouse (ADW)

• ADW architecture and features
• Auto-indexing and auto-partitioning
• Auto-scaling compute and storage
• Loading data into ADW
• ADW performance and monitoring

Module 6: Data Warehouse Performance Tuning

• Query execution plan analysis
• Partition pruning optimization
• Parallel execution tuning
• Result cache in DW
• In-memory column store

Module 7: Oracle In-Memory Database

• In-Memory Column Store architecture
• Enabling in-memory for tables and partitions
• In-memory joins and aggregations
• In-memory advisor
• Performance monitoring for in-memory

Module 8: Data Integration with ODI

• Oracle Data Integrator architecture
• ODI topology and mapping design
• Knowledge modules in ODI
• E-LT approach with ODI
• ODI agent and scheduling

Module 9: Data Quality Management

• Data profiling with Oracle EDQ
• Data cleansing and standardization
• Address validation
• Duplicate detection
• Data quality dashboards

Module 10: Data Governance

• Data governance framework
• Data catalog and metadata management
• Data lineage and impact analysis
• Data stewardship roles
• Oracle Enterprise Data Quality (EDQ)

Module 11: Modern Data Lakehouse

• Data lake concepts and Oracle Object Storage
• Lakehouse architecture on OCI
• Oracle Autonomous Database for lakehouse
• External tables and data virtualization
• Real-time streaming into data warehouse

Module 12: Real-Time Projects and Case Studies

• Enterprise data warehouse design
• ADW implementation on OCI
• End-to-end data warehouse project
• Certification and interview preparation

Experience in the Industry Gain knowledge from experts with hands-on Oracle Data Warehouse project experience in enterprise analytics and BI programs.

Backgrounds at the Top Prominent corporations such as HCL, TCS, Accenture, and Oracle Consulting employ our Data Warehouse trainers.

Clear & Effective Teaching Excellent communication and real-world examples simplify complex dimensional modeling and ETL design.

Hands-On Learning Focus Students apply skills using live Oracle ADW and ODI environments with real data warehouse design and ETL projects.

Up-to-Date Knowledge Trainers stay current with Oracle ADW, Data Lakehouse architecture, and latest cloud data warehousing trends.