Better, faster, smarter: The Case for Data Warehouse Automation
Chris Stewart, WhereScape
Learn how software can be used to solve one of the most pervasive problems in BI today – that is data warehouses take too long to deliver value to the business, and then become too hard to change. The need to store, integrate and prepare data for analysis is not going away – the data warehouse has a bright future, but according to TDWI, building a data warehouse is among the most labor-intensive and time-consuming activities of BI development. There are so many moving parts—requirements, source data analysis, data quality, source-target mapping, data acquisition, data transformation logic, ETL design, scheduling, error handling—and getting it right the first time isn’t easy. And when you finally do get it right, something changes.
The two areas of data warehouse automation include:
- Data warehouse design automation – a design tool that discovers and uses source system structures, rules and standards to accelerate data warehouse design.
- Data warehouse development automation – an IDE that uses metadata to generate and synchronize related development tasks – such as table management, index management, processing (ETL, ELT), documentation, deployment and scheduling. Metadata allows related development tasks to be combined to drastically reduce the time to delivery – and is used to enable agile / iterative development.
Join data warehouse automation pioneer WhereScape for this presentation to learn how companies like VW, Nike, Costco, Expedia, Blue Cross, F5 accelerate warehouse development and change cycles while simultaneously assuring quality and consistency. One of the most important aspects of doing automation right is that it should not get in the way of your developers – it should leverage existing skills, add best practices and generate documentation.
About the Speaker
Chris Stewart is Director of Services for WhereScape and has been designing and implementing data warehouses for the last 20 years. Before joining WhereScape, Chris led data warehouse architecture for several large clinical quality improvement and supply chain companies. During the last decade, he has leveraged the computing power of databases to build large data warehouses without the use of traditional ETL tools.