Prerequisite: This course assumes an understanding of fundamental technology architectures.
Data warehousing used to be IT's weapon of choice for corralling the "islands of data" and bringing order to the decentralized information chaos. However, shifting business priorities, outsourcing’s popularity, and the emergence of a new set of technology solutions have changed the landscape and the complexity of managing the abundance of enterprise data.
Data access and delivery technologies such as EII (enterprise information integration), EAI (enterprise application integration), and ETL (extract, transform, and load) are offering companies ways to be clever and more deliberate about delivering data to systems and users more effectively. And with the emergence of customer data integration (CDI) and master data management (MDM) solutions, there’s an entirely new set of offerings to consider when integrating corporate information from across packaged applications, core platforms, and legacy systems.
In this session, Evan Levy will identify the architectural trade-offs and issues associated with each solution—from performance and functionality to flexibility and efficiency. He will present examples and case studies where these new integration architectures and methods have been implemented. Along the way, he'll pepper the course with architectural examples that illustrate new ways of solving often age-old data integration dilemmas.
You Will Learn
- The standard alternatives for data integration
- EAI, EII, and ETL—and how they’re different
- How data integration solutions and metadata coexist
- How CDI and MDM solve the problem
- Samples of architectures that work
Geared To
- CIOs; data management staff; program and project managers; center of excellence staff; application developers; data warehouse architects; IT architects