Data Warehousing and Integration Part 2

Covers various topics in Data Engineering in support of decision support systems, data analytics, data mining, machine learning, and artificial intelligence. Studies on-premises data warehouse architecture, dimensional modeling of data warehouses, Extract-Transform-Load (ETL) integration from source systems to data warehouse, On-line Analytical Processing (OLAP) systems, and the evolving world of data quality and data governance. Offers students an opportunity to design, develop and maintain cloud-based data pipelines. Both on-premises and cloud-based platforms will be used to illustrate and implement Data Engineering techniques using operational and analytical data warehouses

• Understand on-premises and cloud data warehouse architectures
• Apply dimensional modeling for data warehouses
• Design and implement ETL processes
• Use OLAP systems for data analysis
• Apply data quality and governance concepts
• Develop and maintain cloud-based data pipelines

• Basic computer and internet skills
• Ability to follow course instructions in English and complete exercises