Level: Intermediate to Advanced
Prerequisite: None
This full-day class examines the emergence of new trends in data warehouse implementation and the deployment of analytics ecosystems. Stephen Brobst will discuss new platform technologies such as columnar databases, in-memory computing, and cloud-based infrastructure deployment. He will also examine the concept of a “logical” data warehouse—including an ecosystem of both commercial and open source technologies. Real-time analytics and in-database analytics will also be covered.
The implications of these developments for deployment of analytics capabilities will be discussed with examples in future architecture and implementation. This course also presents best practices for deployment of next-generation analytics using AI and machine learning.
You Will Learn
- Analytics in the cloud
- Data mesh for increased agility in execution
- Interactive analytics using in-memory, columnar, and other advanced database technologies
- Real-time streaming and analytics
- Leveraging open-source technologies such as TensorFlow, R, Spark, Presto, and other emerging solutions
- Data lake construction with use of NoSQL and late-binding analytics architectures
- AI and machine learning
Geared To
- Data architects
- Solution architects
- Big data architects
- BI analysts, business analysts, and data analysts
- Data warehousing and data integration specialists
- Business and IT leaders
- Analytics project managers
- Analytics program managers