Master Data Warehousing, Dimensional Modeling & ETL process
InstructorNikolai Schuler
The curriculum provides deep coverage of star and snowflake schemas, including various types of slowly changing dimensions.
Instruction effectively distinguishes between OLTP and OLAP systems, providing a strong foundation for data warehouse design.
Editorial course preview
These 4 complementary views highlight concrete, legible examples from the course presentation.
This diagram illustrates the architecture of a data warehouse, mapping the progression from raw data sources through staging and core layers to specialized data marts.
This screenshot displays a successful ETL job execution in Pentaho, featuring a visual workflow diagram with completed steps and detailed system logs confirming the process finished without errors.
This slide illustrates the administration of Type 2 Slowly Changing Dimensions using a sample product table that tracks validity periods via effective and expiration date columns.
This educational slide demonstrates database indexing by showing a sales table, a SQL query filtering by customer ID, and visual mappings of how indexes link values to data locations.
Learners have noted that Pentaho installation steps are outdated for newer versions and can present significant difficulties on macOS. This signal predates the displayed course update; the update may have addressed it, but the update label does not prove that it was corrected.
The absence of a cleanup checklist for AWS resources may result in unexpected billing. Although the course has a recent update label, these reports were made before that date and the update does not guarantee a correction.
The course aligns well with the goal of learning data warehouse architecture, but may be difficult for those without a coding background or those on macOS. This signal predates the displayed course update; the update may have addressed it, but the update label does not prove that it was corrected.