Azure Data Processing
Master Azure data processing using Databricks, Data Factory, and Stream Analytics for effective ETL workflows.
Master Azure data processing using Databricks, Data Factory, and Stream Analytics for effective ETL workflows.
This comprehensive course teaches advanced data processing techniques using Microsoft Azure services. Students learn to configure batch processing with Databricks and Data Factory, implement ETL/ELT workflows, and create data pipelines. The curriculum covers essential topics including linked services, streaming analytics, PolyBase integration, and real-time data processing. Through hands-on exercises, learners gain practical experience with Azure tools while developing skills in big data analytics, pipeline automation, and data transformation.
3.7
(67 ratings)
7,513 already enrolled
Instructors:
English
English (Original), Deutsch (Auto), हिन्दी (ऑटो), 18 more
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What you'll learn
Configure batch processing with Databricks and Data Factory
Implement ETL and ELT workflows in Azure
Create and manage data pipelines and triggers
Master streaming analytics and windowing functions
Develop skills in real-time data processing
Skills you'll gain
This course includes:
222 Minutes PreRecorded video
7 assignments, multiple hands-on exercises
Access on Mobile, Tablet, Desktop
FullTime access
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There are 8 modules in this course
This comprehensive course covers advanced data processing techniques in Microsoft Azure. The curriculum spans eight modules, focusing on batch processing with Databricks, pipeline creation in Data Factory, streaming analytics, and data transformation strategies. Students learn to implement ETL/ELT workflows, configure real-time data processing, and utilize Azure services for efficient data management. The course combines theoretical knowledge with practical implementation through hands-on exercises.
Introduction
Module 1 · 7 Minutes to complete
Section 1 - Batch Processing with Databricks and Data Factory on Azure
Module 2 · 2 Hours to complete
Section 2 - Creating Pipelines and Activities
Module 3 · 2 Hours to complete
Section 3 - Link Services and Datasets
Module 4 · 1 Hours to complete
Section 4 - Schedules and Triggers
Module 5 · 1 Hours to complete
Section 5 - Selecting Windowing Functions
Module 6 · 1 Hours to complete
Section 6 - Configuring Input and Output for Streaming Data Solutions
Module 7 · 1 Hours to complete
Section 7 - ELT versus ETL in Polybase
Module 8 · 1 Hours to complete
Fee Structure
Payment options
Financial Aid
Instructors
Distinguished Technology Leader and Digital Transformation Expert
Kenny Mobley serves as a technology leader with 24 years of experience in aligning business strategies with technological solutions. His expertise spans across Fortune 20 companies, mid-sized organizations, and startups, where he has successfully implemented data-driven business practices and optimized organizational processes. As Vice President of Services, he has demonstrated success in creating environments for delivering creative, cost-effective data analytics and cloud-based solutions. His recent accomplishments include leading a transformative cloud migration project for a Fortune 500 retailer's data analytics assets and services. At LearnQuest, he shares his expertise through courses focused on Azure cloud technologies and data processing, helping professionals master cloud computing concepts and implementation strategies.
Instructor
Management & Information Technology Consultant holding Kellogg M.B.A, Six-Sigma Green Belt with extensive experience in business system analysis, software development, quality assurance and project management.
Testimonials
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3.7 course rating
67 ratings
Frequently asked questions
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