Manage and Develop Data Processing Solutions
Lecture
Karen Lopez
Intermediate
1 h 28 m
2020-01-24
Lecture Overview
This course covers configuring, managing and deploying Azure data processing solutions. We start with an overview of big data environments, including Hadoop clusters, then cover how to plan for and implement Azure Databricks, Azure Stream Analytics, Event Hubs, Azure Data Factory and how these fit with Azure Data Warehouse solutions.

Related Learning Path(s):
DP-200: Implementing an Azure Data Solution
Objectives
  • The course demonstrates how to provision and manage Azure data processing, including movement, synchronization and pipelines.
Pre-Requisites
  • An Azure subscription
  • SQL Server Management Studio installed
  • Azure Storage Explorer installed
  • Basic knowledge storage and networking concepts
  • Previous experience with Azure Portal is recommended, but not required.
Lecture Modules
This module focuses on batch processing solutions, including using Data Factory and Azure Databricks, implementing the Integration Runtime for Data Factory, creating Linked Services and Datasets, creating Pipelines and Activities, creating and scheduling Triggers, ingesting data by using PolyBase, Azure Databricks Clusters, Notebooks, Jobs, and Autoscaling, and ingesting data into Azure Databricks.

This module covers covers the implementation of Azure Stream Analytics, Event Hubs and integrating with Azure Data Warehouse. This module will include an overview of Azure Stream Analytics features and concepts, configuring Azure Stream Analytics, event processing using steam analytics, and selecting the appropriate windowing functions.
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