Explore a different approach to building data lakes without relying on clusters in this conference talk. Learn how to run and manage on-demand experiments from scratch in minutes using Azure Data Lake as an example. Discover the advantages of removing cluster maintenance and infrastructure costs from analytical work. Gain insights into storage and analytics, understanding data sources, and the complexities of traditional cluster-based infrastructures. Delve into Azure Data Lake Analytics, including Scope and Sequel, and witness a demonstration of Cognitive Extensions. Understand how to monitor jobs, integrate with Power BI, and avoid common rookie mistakes. By the end of this talk, grasp why this alternative approach to data lakes is worth considering for advanced analytics projects.
Overview
Syllabus
Introduction
Who is Dom
Plan
Data like
Understand what youre after
Supporting data sources
Data lakes
Storage and analytics
Clusters
Head nodes
Worker nodes
Complex infrastructure
Cluster categories
Doityourself cluster
Cloud hosted
Data Breaks
Onprem
Azure Data like analytics
What is Scope
What is Sequel
Azure Data Like Analytics Resource
Azure Data Like Analytics Dashboard
Cognitive Extensions
Demo of Cognitive Extensions
Monitoring jobs
Power BI
C and native jobs
From code
Rookie mistake
Recap
Why should we bother
Taught by
NDC Conferences
