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Data Processing with Azure

Approx. 13 hours to complete

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Course Summary

Learn how to process and analyze data using Azure with this comprehensive course. Gain hands-on experience with Azure services and tools to prepare yourself for a career in data processing.

Key Learning Points

Use Azure services for data processing and analysis
Learn how to work with big data and machine learning
Gain hands-on experience with real-world examples

Learning Outcomes

Understand the fundamentals of Azure data processing
Gain hands-on experience with Azure services and tools
Be able to analyze and process big data using Azure

Prerequisites or good to have knowledge before taking this course

Familiarity with programming concepts
Basic knowledge of data analysis and processing

Course Difficulty Level

Intermediate

Course Format

Online
Self-paced
Hands-on

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Description

This Azure training course is designed to equip students with the knowledge need to process, store and analyze data for making informed business decisions. Through this Azure course, the student will understand what big data is along with the importance of big data analytics, which will improve the students mathematical and programming skills. Students will learn the most effective method of using essential analytical tools such as Python, R, and Apache Spark.

Knowledge

Configure batch processing with Databricks and Data Factory on Azure
Use ETL and ELT to load and transform data
Create linked services and identify pipelines for data stored within Data Factory
Explain Data Virtualization in PolyBase

Outline

Introduction
Course Introduction

Section 1 - Batch Processing with Databricks and Data Factory on Azure
1.1 Batch Processing with Databricks and Data Factory in Azure
1.2 - ELT Processing using Azure
1.3 - Databricks and Azure Spark
1.4 Transform Data using Databricks in ADF
1.5 Use Case: ADF and Spark
Azure Databricks and Apache Spark
Exercise 1 - Use Batch Processing with Databricks and Data Factory on Azure
Exercise 2 - Intro to Databricks and Data Factory Page
Module 1 Quiz

Section 2 - Creating Pipelines and Activities
Pipelines and Activities - Introduction
Processing using a Pipeline
Analyzing Logs for an HDInsight Cluster
Using Azure Blob Storage within HDInsight
Using Azure Blob Storage with HDInsight
Exercise 1 - Pipeline Activities & Usage in Azure Data Factory
Exercise 2 - Examine Logs within the HDInsight/Blob Storage
Module 2 Quiz

Section 3 - Link Services and Datasets
Link Services and Datasets - Introduction
Identifying Pipelines for a Data Factory
Data Stores and Azure Blob Storage
Linked Service and Connecting Data Factory to External Resources
Processing Input Blobs with Azure Data Factory
Exercise 1 - Link Data within Datasets in Azure Storage
Module 3 Quiz

Section 4 - Schedules and Triggers
Schedules and Triggers - Introduction
Creating a Trigger that Runs a Pipeline on a Schedule
Scheduling a Trigger in Azure Data Factory
Pipeline Execution and Triggers in ADF
Use Case: Azure Schedule, Trigger, and Events
Pipeline Execution and Triggers in ADF
Module 4 Quiz

Section 5 - Selecting Windowing Functions
Selecting Windowing Functions - Introduction
How Stream Analytics Support Native Windowing Functions
Temporal Windows
Using Window Functions in the GROUP BY Clause
Aggregating Events over Multiple Windows using WindowsQ
Understanding Stream Analytics Windowing Functions
Module 5 Quiz

Section 6 - Configuring Input and Output for Streaming Data Solutions
How Stream Analytics Relate to Data Solutions
Generate Sample Call Data and Send it to Event Hubs
Creating a Stream Analytics Job
Configuring Job Input and Output
Define a Query to Filter Fraudulent Calls
Test and Start the Job
Visualize Results in Power BI
Output Real-Time Stream Analytics Data to a Power BI Dashboard
Module 6 Quiz

Section 7 - ELT versus ETL in Polybase
ELT vs ETL in PolyBase - Introduction
How SQL Data Warehouse in Microsoft Offers ELT Solutions
Loading Methods using Non-PolyBase Options
Use Case: A Deeper Dive into ETL Processing
Video: Ingesting Data using Polybase | Azure SQL Data Warehouse
Module 7 Quiz

Summary of User Reviews

Learn data processing with Azure in this comprehensive course on Coursera. Users have praised the course for its practical approach and real-world examples.

Key Aspect Users Liked About This Course

The course offers hands-on experience with Azure tools and techniques.

Pros from User Reviews

Practical and applicable course material
Real-world examples and case studies
Hands-on experience with Azure tools
Engaging and knowledgeable instructors
Valuable certification upon completion

Cons from User Reviews

Course can be challenging for beginners
Technical jargon may be difficult to understand
Course material may become outdated quickly
Lack of personal interaction with instructors
Course may require additional resources to fully understand

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