Utilizing Kafka to create a Streaming ETL platform

The landscape of traditional ETL, Business Intelligence and Big Data is changing and the need for data real time or near real time is ever increasing. The move away from batch processing has been underway for a while and several new architecture patterns have emerged to support this move. Those patterns include, but are not limited to, moving to the cloud, microservices and streaming. One of those patterns include using Kafka for real time ingestion and processing. This presentation focuses on utilizing Kafka in a traditional ETL pattern as well as its support for microservice based architecture, Big Data and streaming in general.

Bio:
Chris Barth is a consultant for Pinnacle Solutions Group and possesses over twenty years of professional experience in application architecture, design, development, and support. His specialties include designing, architecting and tuning Data environments, such as streaming platforms, very large SQL Server solutions as well as, but not limited too, Oracle and PostgreSQL solutions. He has also designed and developed business solutions for the retail, banking, health care, and legal industries. Some of his recent experience involves designing and developing streaming solutions and Restful APIs for commercial banking, a Data Warehouse for Marketing Fullfillment and a ODS for a Commercial Banking underwriting.