Analyzing Semi-Structured Data At Volume In The Cloud

The Cloud, Mobile and Web Applications are producing semi-structured data at an unprecedented rate. IT professionals continue to struggle capturing, transforming, and analyzing these complex data structures mixed with traditional relational style datasets using conventional MPP and/or Hadoop infrastructures. Public cloud infrastructures such as Amazon and Azure provide almost unlimited resources and scalability to handle both structured and semi-structured data (XML, JSON, AVRO) at Petabyte scale. These new capabilities coupled with traditional data management access methods such as SQL allow organizations and businesses new opportunities to leverage analytics at an unprecedented scale while greatly simplifying data pipeline architectures and providing an alternative to the "data lake".

Please join DWDC and Snowflake Computing for a discussion of these topics and a demonstration of this game changing technology. The demonstration will focus on analyzing structured and semistructured together using a commercially available cloud based platform and standards based SQL language to provide insights on large petabytes scale data sets.

Our Speaker: Kevin Bair

Kevin Bair is a Solution Architect with extensive experience working with both federal and large commercial organizations over the last 25 years. He has a background in application development, database and content management, virtualization, and operational analytics. His career includes 15 years working for IBM Software Group, ITIL certification, and development of a patent related to Big Data on a virtualized network. Kevin is currently a Solution Architect at Snowflake Computing helping clients and business partners develop enterprise class solutions on AWS using Snowflake's Cloud-based Elastic Data Warehouse.