Azure Data Lake - Summit Preview

Gain a comprehensive understanding of Azure Data Lake technologies in this one-hour conference talk from the PASS Data Community Summit. Learn about the benefits, challenges, and best practices for implementing Azure Data Lake, including its storage and compute services, U-SQL language features, cost optimization techniques, and integration with other Azure services. Explore data virtualization concepts, federated queries, and PolyBase design patterns for effective data management. Discover how to get started with a Data Lake project and leave equipped with essential knowledge to leverage Azure Data Lake in your big data initiatives.

Intro
Technical Assistance
Thank you to our Presenting Sponsor
Agenda Azure Data Lake: What, Why and How
What is a Data Lake?
Data Lake Objectives
Data Lake Use Cases
Big Data in Azure: Storage
Deciding Between Storage Services
Big Data in Azure: Compute
Deciding Between Compute Services
Azure Data Lake Store - a Shared Foundation
Azure Data Lake Store - Distributed File System
Azure Data Lake Analytics (ADLA)
U-SQL: EXTRACT
U-SQL: Single Input File
U-SQL: Multiple Input Files
U-SQL: Built-In Extractors and Outputters
U-SQL: Variables
U-SQL: Processing Rules
U-SQL: Keywords
Cost Model
AU Analyzer to Optimize for Cost and Speed
ADLA Integration with Other Services
Basics of U-SQL Query Execution
Two Types of Tables in ADLA Catalog
Multi-Platform Architecture
Data Lake + Data Warehouse: Inverse Relationship
Why Data Virtualization?
Two Ways to Approach Federated Queries in ADLA
Data Movement vs. Data Virtualization
PolyBase for Data Loading
PolyBase Design Pattern for Data Management
Getting Started with a Data Lake Project
Definitions