The course content is well structured. The lessons' delivery is clear and concise. Apart from that, there is much room for improvement:
The content is very outdated. Also, some of the course material should be rewritten (E.g., I lost count of how many times the course material states something different regarding which RDBMSs can be used for the assignment).
Many topics are presented using Excel or Excel-equivalents:
(a) In module 2, WebPivotTable is used to explain data cubes. WebPivotTable is just Excel pivot tables in a web interface.
(b) In module 3, the assignment tasks us with designing a data warehouse through the combination of a database and an unstructured Excel file. In real business settings, Excel files created and maintained by users should never be used as sources for operational databases/data warehouses, especially by combining them with data produced and maintained by operational IT systems.
(c) In module 5, the Pentaho assignment tasks us with loading Excel and Access files to a database. Data integration tools in real life are used to combine data sources coming from different IT systems and combining them into a single (Or multiple) data warehouse. The process of loading data from a file into a database is a trivial task, and is not handled by tools such as Pentaho. Thus, I think a more representative example should be used to demonstrate the tool's usage.
Topics that I would like to see covered in a course such as this:
(a) More in depth presentation of relational data warehouse schema design.
(b) Presentation of different types of data integration and use cases for each (Batch vs real time).
(c) Presentation of modern data engineering tools, e.g. cloud data warehouse offerings (Amazon Redshift, Google BigQuery, Snowflake, e.tc.), data integration tools (Apache Kafka, Apache Airflow), infrastructure as code tools (Ansible, Terraform, e.tc.) and their usage in data warehouse implementations, programming languages used for data pipeline design (Python, Scala, e.tc.), NoSQL databases and their usage in data engineering.