Data integration is usually the slowest and most complex part of any data environment, whether it’s a one-off analytics project done by end users or a data warehouse built by IT. The market for data integration is in the midst of change as new technologies challenge assumptions about how integration should be done and who can do the work. It’s now possible for analysts to access, clean, and analyze data without IT involvement.
This course focuses on some of the tools and technologies that speed up the process of delivering data to users. Some of these are analyst focused, like self-service data preparation and analysis tools. Others are focused on challenges in the technology architecture, enabling IT to make data available more quickly.
Topics in this session include self-service data integration, data preparation, exploratory profiling, data virtualization, automation, testing and test data management, making streaming data available to nonprogrammers, and rethinking assumptions about data integration and architecture. This course will include demos of some of the tools discussed.
You Will Learn
- The latest innovations for integrating and preparing data
- How these new technologies fit into your environment
- What to look for when evaluating these new technologies
- Architects, analysts, and BI managers who want to understand the new integration technologies