Implementing an Azure Databricks Environment in Microsoft Azure
Course info



Course info



Description
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
Section Introduction Transcripts
Course Overview
[Autogenerated] Hi, everyone. My name is Michael Better and welcome my course. Implementing Azure data bricks in Microsoft Azure. I'm an author. Evangelist Set quarrel site. Working with Big Data's a challenge as your data. Burt's makes spinning up resource is to solve your big data analysis issues quick and easy. With this course, you'll gain the ability to implement azure data birds for use by all of your data consumers like business users and data scientists. Some of the major topics that will cover include fundamental components of azure data. Berks working with data and data bricks, notebooks, building an ML scoring pipeline and ingesting streaming data. By the end of this course, you'll have the skills and knowledge of azure data bricks needed to implement data pipeline solutions For your data consumers before beginning the course, you should be familiar with building and employing azure data solutions like Azure sequel, Azure sequel, Data Warehouse and as your Data Lakes. You should be ableto understand machine learning concepts and model building techniques and also know a common language like python scallop are for sequel for working with data. From here, you should feel comfortable diving into azure data pipelines with courses on batch scoring, Azure Dev ops and Azure Automation. I hope you'll join me on this journey to learn azure data bricks with the implementing Azure data breaks in Microsoft Azure course at Biocyte.