Learn about the major cloud data platforms, their abilities to support the modern data warehouse, key architectural features, and how to choose the platform that is right for your business. Richard Winter and Norbert Kremer, experts in data management at scale, walk you through everything you need to know about cloud data platforms and architecture.
Conference Replay | Digital Course Book Included
The 2020s are going to require a modern data warehouse to meet demanding new requirements for machine learning, data variety, scale, and real-time analytics—and this will often be implemented in part or in its entirety in the cloud.
In this course, you will learn about the major data warehouse platforms, their abilities to support the modern data warehouse, key architectural features, and what makes them different from one another. With a focus on data warehousing in the cloud, this course will help you understand why data warehouse platforms are scalable in different ways.
This course will give you the technical reasons why scaling up is sometimes easy and sometimes very hard—at a level that architects, strategists, and decision makers can understand. You need this understanding to choose the best platform for your cloud data warehouse or workload—and to avoid platform mistakes that can be catastrophic.
You Will Learn
- Key concepts for modern data warehouses
- Platform architecture and scalability
- Performance and cost
- Workload requirements and how to apply them in selection
- Data and analytics variety
- Machine learning and advanced analytics inside the data warehouse
- Near real-time data and analytics
- Relevant features of leading cloud data warehouse platforms such as AWS Redshift, Azure SQL, Cloudera Data Warehouse, Google BigQuery, Oracle ADW, Snowflake, Teradata, and Yellowbrick
- Data architects
- Data strategists
- Decision recommenders/decision makers
- Data analysts/data scientists
- Project managers
- Enterprise/cloud architects
Continuing Professional Education Credits: 4
Apply these credits toward your CBIP recertification. Not certified? Learn more about CBIP and how to get certified here.
A specialist in the technology and implementation of analytic data management at scale, Richard Winter advises clients on data strategy and data architecture, focusing on the modern data warehouse and the data lake, frequently in the cloud. He has been retained to make architecture and platform recommendations or perform engineering tests for more than 50 leading enterprises, government agencies, and technology vendors.
Dr. Norbert Kremer is a cloud solution architect with extensive hands-on experience designing and building large-scale data warehouse and big data solutions incorporating machine learning and AI on structured and unstructured data, both on premises and in the cloud. Dr. Kremer has years of experience with widely used data warehouse platforms and is a Google Certified Professional Data Engineer and Cloud Engineer, a Google Authorized Trainer, and an AWS Certified Data Architect.