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TDWI San Diego Update

At TDWI, we have been working hard to navigate this ever-changing landscape in the face of COVID-19, and we want to assure you that the health and well-being of our employees, customers, and vendor partners is our top priority. Therefore, we have unfortunately decided to cancel TDWI San Diego 2020.

We truly appreciate your support during this difficult time. Our registration team will be in contact with individual registrants and sponsors directly. View our virtual learning options at tdwi.org/virtualtraining.

Course Description

M3A Modern Data Warehouse Platforms and Architectures for the CloudNEW!

August 17, 2020

9:00 am - 12:15 pm

Duration: Half Day Course

Level: Intermediate to Advanced

Prerequisite: Familiarity with data warehousing concepts and requirements.

Dr. Norbert Kremer

Norbert Kremer, Ph.D.

Sr. Director, Cloud Data Warehousing & Analytics

WinterCorp

Richard Winter

Richard Winter

CEO & Principal Consultant

WinterCorp

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 of 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

Geared To

  • Data architects
  • Data strategists
  • Decision recommenders/decision makers
  • Data analysts/data scientists
  • Project managers
  • Enterprise/cloud architects