Building a data warehouse is among the most labor-intensive and time-consuming activities of BI development. There are many moving parts—requirements, source data analysis, source-target mapping, data acquisition, data transformation logic, ETL design, database loading, scheduling, error handling—and getting it right the first time isn’t easy. When you finally do get it right, something changes. One of the most pervasive problems in BI today is the fact that data warehouses take too long to build and they are hard to change!
Data warehouse automation (DWA) is a relatively new class of technology that accelerates warehouse development and change cycles while simultaneously assuring quality and consistency. More than simply generating ETL scripts, DWA automates the entire life cycle from source system analysis to testing and documentation. Productivity gains, cost savings, and quality improvement are all possible with DWA.
BI and data warehousing program and project managers; data integration architects, designers, and developers; data warehouse operations, maintenance, and support personnel; data and technology architects.
Module 1 – Data Warehouse Automation Concepts and Principles
Modue 2 – Building and Managing the Data Warehouse
Module 3 – Using Data Warehouse Automation
Module 4 – Data Warehouse Automation in Action
Module 5 – Getting Started with Data Warehouse Automation