Implementing an Azure Databricks Environment in Microsoft Azure
Everyday we have more data, and the problem is how do we get to where we can use the data. Learn how Azure Databricks helps solve those data problems with a robust analytics platform for bringing your data together for data engineers and scientists.
What you'll learn
Every day, we have more and more data, and the problem is how do we get to where we can use the data for business needs. In this course, Implementing a Databricks Environment in Microsoft Azure, you will learn foundational knowledge and gain the ability to implement Azure Databricks for use by all your data consumers like business users and data scientists. First, you'll learn the basics of Azure Databricks and how to implement ts components. Next, you will discover how to work with Azure Databricks during ETL (Extract, Transform, Load) operations. Then, you'll move on to performing batch scoring with machine learning models. Finally, you will explore how to work with streaming data from HDInsight Kafka. When you’re finished with this course, you will have the skills and knowledge of Azure Databricks needed to implement data pipeline solutions for your data consumers. Software required: Microsoft Azure Subscription
Table of contents
- Overview 2m
- Machine Learning Intro 4m
- Apache Spark Machine Learning Libray 1m
- Implementing a Batch Scoring Pipeline 2m
- Predictive Maintenance Batch Scoring 3m
- Demo: Performing Batch Scoring in Azure Databricks Setup 2m
- Demo: Setting up a Batch Scoring Environment 2m
- Demo: Ingesting Data into Azure Databricks 1m
- Demo: Implementing Feature Engineering 3m
- Demo: Build ML Models 1m
- Demo: Modeling Data in Azure Databricks 3m
- Demo: Add Batch Scoring Job for Scoring Pipeline 4m
- Summary 2m
- Overview 1m
- Apache Kafka on Azure HDInsight 3m
- Demo: Building a HDInsight Kafka Cluster 4m
- Demo: Configuring Kafka for IP Advertising 3m
- Demo: Create a Kafka topic 2m
- Demo: Building and Configuring an Azure Databricks Cluster 2m
- Virtual Network Peering 3m
- Azure Databricks and Streaming Data 1m
- Producing Events and Consuming Data with Azure Databricks Notebooks 5m
- Summary 1m