What experience level is required for Building Streaming Data Pipelines in Microsoft Azure?

This course is aimed at the Intermediate level. Having some basic understanding of the topic will help you get the most out of the curriculum.

How long does it take to complete Building Streaming Data Pipelines in Microsoft Azure?

The total duration of the course is approximately 3 hour 2 minutes. Since it is generally self-paced, completion time depends entirely on your learning schedule and availability.

Is this course more theory-focused or project-focused?

This course provides a strong mix of conceptual theory and practical application to ensure a comprehensive understanding of the subject matter.

What careers is this course relevant for?

The skills taught in this course are highly relevant for professionals pursuing roles within Data Science and adjacent technical fields looking to upskill.

Data Science

Building Streaming Data Pipelines in Microsoft Azure

Name: Building Streaming Data Pipelines in Microsoft Azure
Availability: InStock
Rating: 4 (59 reviews)

Do you need to process live data streams from sensors, custom apps, IoT devices, and logs? Do you need to immediately respond to anomalies and patterns in live data streams? Are you familiar with T-SQL? If so, Azure Stream Analytics is for you.

Intermediate FriendlySelf-Paced Learning

Reviews ( 59 )

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🧠 Good for intermediate learners

⚠ May feel basic for advanced users

Learning Journey Context

Works well as a continuation after mastering Data Science fundamentals. It bridges the gap toward advanced, production-level engineering.

Career Relevance

Relevant for: Cloud Engineer, DevOps Engineer, Solutions Architect.

💡This course fits perfectly into our comprehensiveData Science Learning Path. Explore the ecosystem to see how it compares to other foundational skills.

Quick Facts

3 hour 2 minutes

pluralsight

Intermediate

Self-Paced Online

Core Courses

pluralsight

English

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What You’ll Learn

Processing live data streams in real time can be challenging and expensive. In this course, Building Streaming Data Pipelines in Microsoft Azure, you will gain the ability to effectively use Azure Stream Analytics for your live data processing needs. First, you will learn to configure stream and reference inputs for the service. Next, you will discover how to process your data using the Stream Analytics Query Language. Finally, you will explore how to visualize Azure Stream Analytics output with Microsoft Power BI. When you are finished with this course, you will have the skills and knowledge of Azure Stream Analytics needed to turn your live stream data into meaningful, actionable information.

See how this course curriculum compares with alternatives

Outcomes

Course Overview : 1min.
Azure Stream Analytics Overview : 42mins.
Configure Azure Stream Analytics with Event Hub and Blob Storage Inputs : 23mins.
Query Data Using Azure Stream Analytics : 44mins.
Implement Azure Stream Analytics Data Visualization with PowerBI : 20mins.
Anomaly Detection in Azure Stream Analytics : 27mins.
Analyzing Stream Data Using Azure Data Explorer : 23mins.