Data Engineering on Microsoft Azure

Course Description

Data Engineering on Microsoft Azure course covers data solutions, security, analytics, and machine learning using Azure services like Synapse, Databricks, and Stream Analytics. With hands-on labs, it equips professionals to build scalable, secure data systems for business insights.

Curriculum for this course

23 Lessons

Module 1: Get started with data engineering on Azure

3 Lessons

Introduction to data engineering on Azure
.
Introduction to Azure Data Lake Storage Gen2
.
Introduction to Azure Synapse Analytics
.

Module 2: Build data analytics solutions using Azure Synapse Analytics serverless SQL pools

3 Lessons

Use a serverless SQL pool to query files in a data lake
.
Use a serverless SQL pool to transform data
.
Create a lake database
.

Module 3: Perform data engineering with Azure Synapse Apache Spark Pools

3 Lessons

Analyze data with Apache Spark in Azure Synapse Analytics
.
Transform data with Apache Spark in Azure Synapse Analytics
.
Use Delta Lake in Azure Synapse Analytics
.

Module 4: Work with data warehouses using Azure Synapse Analytics

2 Lessons

Analyze data in a relational data warehouse
.
Load data into a relational data warehouse
.

Module 5: Transfer and transform data with Azure Synapse Analytics Pipelines

2 Lessons

Build a data pipeline in Azure Synapse Analytics
.
Use Spark Notebooks in an Azure Synapse Pipeline
.

Module 6: Work with hybrid transactional and analytical processing (HTAP) Solutions using Azure Synapse Analytics

2 Lessons

Plan hybrid transactional and analytical processing
.
: Implement Azure Synapse Link with Azure Cosmos DB Lesson03: Implement Azure Synapse Link for SQL
.

Module 7: Implement a data streaming solution with Azure Stream Analytics

3 Lessons

Get started with Azure Stream Analytics
.
Get started with Azure Stream Analytics
.
Visualise real-time data with Azure Stream Analytics and Power BI
.

Module 8: Govern data across an enterprise

2 Lessons

Introduction to Microsoft Purview
.
Integrate Microsoft Purview and Azure Synapse Analytics
.

Module09: Data engineering with Azure Databricks

3 Lessons

Explore Azure Databricks
.
Use Apache Spark in Azure Databricks
.
Run Azure Databricks notebooks in Azure Data Factory
.

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Course rating

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Reviews

Ruma Sriwastav
Cover all my needs
The course identify things we want to change and then figure out the things that need to be done to create the desired outcome. The course helped me in clearly define problems and generate a wider variety of quality solutions. Support more structures analysis of options.

All Courses

Skills Offered

Emerging Skills Offered by Alchemy for 2024-2025

Data Science & Analytics

Advanced Data Engineering (e.g., Snowflake, Databricks)
Real-Time Data Streaming (e.g., Kafka, Flink)
Predictive Analytics with AI/ML Models
Advanced Business Intelligence Tools (e.g., Power BI, Tableau)

Emerging Programming Frameworks

Quantum Computing Basics (IBM Qiskit, Google Cirq)
Web3 Development: Solidity, Smart Contracts
Low-code/No-code Platforms (OutSystems, Mendix)

Infrastructure Modernization

Software-Defined Networking (SDN) and NFV
Advanced Virtualization (Citrix, VMware updates)
Hybrid and Edge Computing

Soft Skills and Leadership in Tech

Agile Transformation and Leadership
Design Thinking for Problem Solving
Leading AI-Driven Innovation

AI & Machine Learning

Generative AI (e.g., ChatGPT, Bard, MidJourney integrations)
Machine Learning Operations (MLOps)
Advanced NLP and Speech Recognition
AI for Edge Computing

Cloud Technologies

Multi-Cloud Management: Azure, AWS, GCP integrations
Cloud-Native Development: Kubernetes, Docker, Serverless Architectures
AI and ML integration in Cloud Platforms
FinOps: Cloud Cost Management

Cybersecurity

Zero Trust Architecture (e.g., Illumio)
Incident Response and Threat Intelligence
Cloud Security (AWS, Azure, and GCP-focused)
Advanced Penetration Testing and Ethical Hacking

DevOps and DevSecOps

Infrastructure as Code (IaC) with Terraform and Ansible
GitOps and Continuous Integration/Continuous Delivery (CI/CD)
Security in DevOps Pipelines

Data Science & Analytics

Advanced Data Engineering (e.g., Snowflake, Databricks)
Real-Time Data Streaming (e.g., Kafka, Flink)
Predictive Analytics with AI/ML Models
Advanced Business Intelligence Tools (e.g., Power BI, Tableau)

Emerging Programming Frameworks

Quantum Computing Basics (IBM Qiskit, Google Cirq)
Web3 Development: Solidity, Smart Contracts
Low-code/No-code Platforms (OutSystems, Mendix)

Infrastructure Modernization

Software-Defined Networking (SDN) and NFV
Advanced Virtualization (Citrix, VMware updates)
Hybrid and Edge Computing

Soft Skills and Leadership in Tech

Agile Transformation and Leadership
Design Thinking for Problem Solving
Leading AI-Driven Innovation

AI & Machine Learning

Generative AI (e.g., ChatGPT, Bard, MidJourney integrations)
Machine Learning Operations (MLOps)
Advanced NLP and Speech Recognition
AI for Edge Computing

Cloud Technologies

Multi-Cloud Management: Azure, AWS, GCP integrations
Cloud-Native Development: Kubernetes, Docker, Serverless Architectures
AI and ML integration in Cloud Platforms
FinOps: Cloud Cost Management

Cybersecurity

Zero Trust Architecture (e.g., Illumio)
Incident Response and Threat Intelligence
Cloud Security (AWS, Azure, and GCP-focused)
Advanced Penetration Testing and Ethical Hacking

DevOps and DevSecOps

Infrastructure as Code (IaC) with Terraform and Ansible
GitOps and Continuous Integration/Continuous Delivery (CI/CD)
Security in DevOps Pipelines