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Big Data Analytics on Azure

Follow hands-on examples to import data, run queries, and output the results using Azure Databricks, Azure Data Lake Storage Gen2, and Azure Stream Analytics.
Intermediate
Up to 9h 56m
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13 steps
There are 7 Courses in this learning path
There are 5 Hands-on Labs in this learning path
There is 1 Exam in this learning path
COURSE
Intermediate
Duration: 28 minutes and 2 seconds
Introduction to Azure Synapse Analytics
This lesson introduces Microsoft’s Azure Synapse Analytics, covering serverless SQL pools, dedicated SQL pools, Spark pools, and Synapse Pipelines.
HANDS-ON LAB
Intermediate
Duration: Up to 1 hour and 45 minutes
Using Azure Synapse Analytics to Query Data Lake
Learn how to deploy and use Azure Synapse Analytics to query data stored in a data lake through T-SQL statements using a serverless SQL pool in this hands-on lab.
COURSE
Intermediate
Duration: 21 minutes and 41 seconds
Running Spark on Azure Databricks
In this lesson, we will show you how to set up a Databricks cluster and run interactive queries and Spark jobs on it.
COURSE
Advanced
Duration: 38 minutes and 32 seconds
Using Azure Data Lake Storage Gen2
In this lesson, you will follow hands-on examples to import data into Azure Data Lake Storage Gen2 and then securely access it and analyze it using Azure Databricks. You will also learn how to monitor and optimize your Azure Data Lake Storage Gen2.
HANDS-ON LAB
Beginner
Duration: Up to 1 hour
Using Azure Databricks to Import and Analyze Data
Learn to implement lightning-fast analytics by building an Azure Databricks workspace and cluster to interact with Azure Data Lake Store Gen2 data.
COURSE
Intermediate
Duration: 13 minutes and 6 seconds
Introduction to Delta Lake on Azure Databricks
This lesson provides an introduction to Delta Lake in Azure Databricks and shows you how to use it.
COURSE
Intermediate
Duration: 1 hour and 5 minutes
Designing Data Flows in Azure
In this Lesson, we're going to review the features, concepts, and requirements that are necessary for designing data flows and how to implement them in Microsoft Azure.
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