Data Warehouse Training
Learn data warehousing, ETL pipelines, and cloud-based analytics systems. Master the architecture and design of enterprise data solutions.
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Data Warehouse Curriculum
- Core Concepts: OLTP vs. OLAP Systems
- Data Warehouse Architecture: Tiered Structure & Components
- Introduction to Dimensional Modeling: Star & Snowflake Schemas
- Understanding ETL (Extract, Transform, Load) vs. ELT
- Data Cleaning, Profiling & Normalization Techniques
- Introduction to Popular ETL Tools: Informatica, Talend, and SSIS
- Designing Fact & Dimension Tables
- Handling Slowly Changing Dimensions (SCD Type 1, 2, 3)
- Aggregates, Hierarchies & Data Mart Design
- Advanced SQL: Window Functions, CTEs & Recursive Queries
- Query Optimization for Large Datasets
- Writing Complex Stored Procedures & User Defined Functions
- Cloud Architecture Overview: AWS Redshift, Google BigQuery, Snowflake
- Data Loading Strategies in the Cloud (S3/GCS to Warehouse)
- Serverless Data Warehousing & Scaling Strategies
- Data Quality Frameworks & Business Glossaries
- Metadata Catalogs & Data Lineage Tracing
- Implementing Master Data Management (MDM) Principles
- Data Lake vs. Data Warehouse vs. Data Lakehouse
- Building Real-time Data Warehouses with CDC (Change Data Capture)
- Security & Compliance: Data Masking, Encryption & Access Control
- Connecting BI Tools (Power BI, Tableau) to the Warehouse
- Designing Optimized Semantic Layers for Reporting
- Building Automated Data Refresh & Alerting Workflows