Building a data warehouse is an expensive affair and it often takes months to build one from scratch. There is also a constant struggle to keep up with the large volumes of data that is constantly generated. On top of that, setting up a strong architectural foundation, working on repetitive and mundane data validation tasks and ensuring data accuracy is another challenge. This puts tremendous stress on data teams and data warehouses. Data warehouse automation is intended to handle this growing complexity.

Data Warehouse Automation helps IT teams deliver better and faster results by getting rid of repetitive design, deployment and operational tasks within the data warehouse lifecycle. With automation, organizations can accelerate the data to the analytics journey, work more effectively with large amounts of data and save cost.

In this session you will learn:

• The Need and Scope for Data Warehouse Automation
• Key Factors and Tools to Consider for Implementing Data Warehouse Automation
• Practical Steps for the Successful Implementation of an Automated Data Warehouse
• The Future of Data Warehouse Automation