Data Engineering on Microsoft Azure Course
Build your Skills with DevOpsSchool Certification Training Course Online, Azure Cloud Architect Technologies & helps you become an Azure expert ➔ Learn how to manage Azure resources, and configure and deploy virtual machines. ✔️Enroll now!!
Last updated
Self-paced video
Billed yearly at ₹9,996. Includes complete LMS access for one year, access across the DevOpsSchool course library, 20+ additional courses and 50+ tools. Where a course family has four levels, all levels are included by default.
Live & Interactive
Instructor-led live session, max 8 to 10 hours, with demos, labs, Q&A, practical review and certificate support.
1:1 Live training
The same agenda, taught one-to-one by the trainer. Start immediately, without waiting for the next batch. Max 8 to 10 hours, one-to-one.
- Practical demonstrations and guided examples
- Complete LMS access for one year
- Certificate and learning record support
- Corporate customization available
Practical Data Engineering on Microsoft Azure Course learning for professionals and teams.
Build your Skills with DevOpsSchool Certification Training Course Online, Azure Cloud Architect Technologies & helps you become an Azure expert ➔ Learn how to manage Azure resources, and configure and deploy virtual machines. ✔️Enroll now!!
What this program covers
This page is structured for learners who need a focused course, certification topic, platform module, product feature, security area or role-specific skill that may not map directly to Foundation, Essential, Intermediate or Advanced levels.
The learning experience still follows DevOpsSchool standards: concept clarity, practical use cases, demonstrations, hands-on tasks, assessment guidance, certification support and post-session LMS access.
Private Data Engineering on Microsoft Azure Course training for teams and organizations.
DevOpsSchool can align this program to team maturity, current tools, role expectations, compliance requirements, delivery workflow and implementation goals.
- Private online or classroom batch options
- Role-based coverage for engineers, administrators, leads and managers
- Examples can be mapped to internal platforms and use cases
- Useful for onboarding, migration, governance, certification readiness and adoption
Why DevOpsSchool
DevOpsSchool combines practitioner-led explanation, live demonstrations, assignments, LMS access, certificate support and guidance for both individual professionals and corporate teams.
Request corporate proposalThe same course architecture, adapted to this focused topic.
Specialized pages keep the same decision structure as standard level pages, but the content is adjusted to the course objective.
Concepts
Terminology, purpose, architecture, scope and fit inside modern delivery workflows.
Implementation
Configuration, usage patterns, workflows, operating practices and common mistakes.
Integration
Automation, integration touchpoints, delivery process and production readiness.
Validation
Labs, assignments, review questions, certificate support and next-step learning guidance.
Live, self-paced and corporate delivery options.
Fees are intentionally shown only in the hero and once again after the agenda. This section focuses on delivery fit.
| Mode | Duration / access | Best fit |
|---|---|---|
| Self-paced video | One year LMS access | Learners who want flexible pace and broad catalog access. |
| Live & Interactive | Max 8 to 10 hours | Learners who want demos, guided discussion, labs and Q&A. |
| 1:1 Live training | Max 8 to 10 hours, one-to-one | Learners who want to start immediately, at their own pace, with the full attention of the trainer. |
| Corporate | Private team batch | Teams needing customized examples, adoption guidance and rollout support. |
Why this course, what you will achieve, and who should attend.
Use these sections to decide whether the program matches your role, current experience and expected responsibilities.
Why this matters
Data Engineering on Microsoft Azure Course helps learners build practical confidence in a focused technical, certification or platform topic instead of only reading generic documentation.
Objectives
- Understand the core concepts and usage model.
- Apply practical workflows through examples and guided tasks.
- Prepare for implementation, certification or team adoption needs.
Pre-requisites
Basic computer literacy and awareness of software, operations, cloud, DevOps or security workflows is helpful. Deep programming experience is not mandatory unless the topic specifically requires it.
Who should attend
Developers, DevOps engineers, administrators, SREs, security engineers, platform teams, release teams, technical leads and corporate teams working with this topic.
Small-batch live training and flexible self-paced access.
Choose live guidance when discussion and lab review matter, or use self-paced access when schedule flexibility matters more.
Live cohort
Instructor-led sessions with demos, guided examples and Q&A for practical adoption.
Ask for next batchSelf-paced route
Use LMS access for flexible learning, revision and continued access to DevOpsSchool course materials.
Review access modelFocused agenda for Data Engineering on Microsoft Azure Course.
Course-specific agenda topics are preserved and organized for the current program objective while staying in the same page architecture.
Day 1Stage 1
- Module 1: Explore compute and storage options for data engineering workloads
- Introduction to Azure Synapse Analytics
- Describe Azure Databricks
- Introduction to Azure Data Lake storage
- Describe Delta Lake architecture
- Work with data streams by using Azure Stream Analytics
- Combine streaming and batch processing with a single pipeline
- Organize the data lake into levels of file transformation
- Index data lake storage for query and workload acceleration
- Describe Azure Synapse Analytics
- Describe Azure Data Lake storage
- Describe Azure Stream Analytics
- Module 2: Design and implement the serving layer
- Design a multidimensional schema to optimize analytical workloads
- Code-free transformation at scale with Azure Data Factory
- Populate slowly changing dimensions in Azure Synapse Analytics pipelines
- Design a star schema for analytical workloads
- Populate slowly changing dimensions with Azure Data Factory and mapping data flows
- Populate a slowly changing dimensions with Azure Data Factory and mapping data flows
- Module 3: Data engineering considerations for source files
- Design a Modern Data Warehouse using Azure Synapse Analytics
- Secure a data warehouse in Azure Synapse Analytics
- Managing files in an Azure data lake
- Securing files stored in an Azure data lake
- Module 4: Run interactive queries using Azure Synapse Analytics serverless SQL pools
- Explore Azure Synapse serverless SQL pools capabilities
- Query data in the lake using Azure Synapse serverless SQL pools
- Create metadata objects in Azure Synapse serverless SQL pools
- Secure data and manage users in Azure Synapse serverless SQL pools
- Query Parquet data with serverless SQL pools
- Create external tables for Parquet and CSV files
- Create views with serverless SQL pools
- Secure access to data in a data lake when using serverless SQL pools
- Configure data lake security using Role-Based Access Control (RBAC) and
- Access Control List
- Understand Azure Synapse serverless SQL pools capabilities
Day 2Stage 2
- Module 5: Explore, transform, and load data into the Data Warehouse using Apache Spark
- Understand big data engineering with Apache Spark in Azure Synapse Analytics
- Ingest data with Apache Spark notebooks in Azure Synapse Analytics
- Transform data with DataFrames in Apache Spark Pools in Azure Synapse
- Analytics
- Integrate SQL and Apache Spark pools in Azure Synapse Analytics
- Perform Data Exploration in Synapse Studio
- Ingest data with Spark notebooks in Azure Synapse Analytics
- Transform data with DataFrames in Spark pools in Azure Synapse Analytics
- Integrate SQL and Spark pools in Azure Synapse Analytics
- Describe big data engineering with Apache Spark in Azure Synapse Analytics
- Module 6: Data exploration and transformation in Azure Databricks
- Describe Azure Databricks
- Read and write data in Azure Databricks
- Work with DataFrames in Azure Databricks
- Work with DataFrames advanced methods in Azure Databricks
- Use DataFrames in Azure Databricks to explore and filter data
- Cache a DataFrame for faster subsequent queries
- Remove duplicate data
- Manipulate date/time values
- Remove and rename DataFrame columns
- Aggregate data stored in a DataFrame
- Module 7: Ingest and load data into the data warehouse
- Use data loading best practices in Azure Synapse Analytics
- Petabyte-scale ingestion with Azure Data Factory
- Perform petabyte-scale ingestion with Azure Synapse Pipelines
- Import data with PolyBase and COPY using T-SQL
- Module 8: Transform data with Azure Data Factory or Azure Synapse Pipelines
- Data integration with Azure Data Factory or Azure Synapse Pipelines
- Code-free transformation at scale with Azure Data Factory or Azure Synapse Pipelines
- Execute code-free transformations at scale with Azure Synapse Pipelines
- Create data pipeline to import poorly formatted CSV files
- Create Mapping Data Flows
- Perform data integration with Azure Data Factory
- Perform code-free transformation at scale with Azure Data Factory
Day 3Stage 3
- Module 9: Orchestrate data movement and transformation in Azure Synapse Pipelines
- Orchestrate data movement and transformation in Azure Data Factory
- Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines
- Orchestrate data movement and transformation in Azure Synapse Pipelines
- Module 10: Optimize query performance with dedicated SQL pools in Azure Synapse
- Optimize data warehouse query performance in Azure Synapse Analytics
- Understand data warehouse developer features of Azure Synapse Analytics
- Understand developer features of Azure Synapse Analytics
- Improve query performance
- Module 11: Analyze and Optimize Data Warehouse Storage
- Analyze and optimize data warehouse storage in Azure Synapse Analytics
- Check for skewed data and space usage
- Understand column store storage details
- Study the impact of materialized views
- Explore rules for minimally logged operations
Day 4Stage 4
- Module 12: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link
- Design hybrid transactional and analytical processing using Azure Synapse Analytics
- Configure Azure Synapse Link with Azure Cosmos DB
- Query Azure Cosmos DB with Apache Spark pools
- Query Azure Cosmos DB with serverless SQL pools
- Query Azure Cosmos DB with Apache Spark for Synapse Analytics
- Query Azure Cosmos DB with serverless SQL pool for Azure Synapse Analytics
- Query Azure Cosmos DB with Apache Spark for Azure Synapse Analytics
- Query Azure Cosmos DB with SQL serverless for Azure Synapse Analytics
- Module 13: End-to-end security with Azure Synapse Analytics
- Secure a data warehouse in Azure Synapse Analytics
- Configure and manage secrets in Azure Key Vault
- Implement compliance controls for sensitive data
- Secure Azure Synapse Analytics supporting infrastructure
- Secure the Azure Synapse Analytics workspace and managed services
- Secure Azure Synapse Analytics workspace data
- Module 14: Real-time Stream Processing with Stream Analytics
- Enable reliable messaging for Big Data applications using Azure Event Hubs
- Work with data streams by using Azure Stream Analytics
- Ingest data streams with Azure Stream Analytics
- Use Stream Analytics to process real-time data from Event Hubs
- Use Stream Analytics windowing functions to build aggregates and output to Synapse Analytics
- Scale the Azure Stream Analytics job to increase throughput through partitioning
- Repartition the stream input to optimize parallelization
Day 5Stage 5
- Module 15: Create a Stream Processing Solution with Event Hubs and Azure Databricks
- Process streaming data with Azure Databricks structured streaming
- Explore key features and uses of Structured Streaming
- Stream data from a file and write it out to a distributed file system
- Use sliding windows to aggregate over chunks of data rather than all data
- Apply watermarking to remove stale data
- Connect to Event Hubs read and write streams
- Module 16: Build reports using Power BI integration with Azure Synapase Analytics
- Create reports with Power BI using its integration with Azure Synapse Analytics
- Integrate an Azure Synapse workspace and Power BI
- Optimize integration with Power BI
- Improve query performance with materialized views and result-set caching
- Visualize data with SQL serverless and create a Power BI report
- Module 17: Perform Integrated Machine Learning Processes in Azure Synapse Analytics
- Use the integrated machine learning process in Azure Synapse Analytics
- Create an Azure Machine Learning linked service
- Trigger an Auto ML experiment using data from a Spark table
- Enrich data using trained models
- Serve prediction results using Power BI
Choose self-paced library access or live interactive delivery.
This is the second and final pricing block on the page, placed after the agenda so learners can review scope before making a decision.
Self-paced video
Billed yearly at ₹9,996. Includes complete LMS access for one year, access across the DevOpsSchool course library, 20+ additional courses and 50+ tools. Where a course family has four levels, all levels are included by default.
Live & Interactive
Instructor-led live session, max 8 to 10 hours, with demos, labs, Q&A, practical review and certificate support.
1:1 Live training
The same agenda, taught one-to-one by the trainer. Start immediately, without waiting for the next batch. Max 8 to 10 hours, one-to-one.
- Start immediately: no waiting for the monthly batch.
- One learner, one trainer: full attention on your questions.
- Sessions planned around your working hours.
- Your pace, with examples from your own projects and tools.
Method of training and assessment.
The program emphasizes practical demonstration, guided examples and assignment-based validation instead of passive lecture-only learning.
| SL | Method | Weightage |
|---|---|---|
| 1 | Problem-space understanding | 10% |
| 2 | Concept discussion | 15% |
| 3 | Live demo and walkthrough | 25% |
| 4 | Lab and hands-on exercises | 40% |
| 5 | Review and readiness discussion | 10% |
Hands-on learning remains part of the program story.
The exact exercises depend on the topic, but every program should make practical execution visible.
Setup walkthrough
Understand access, environment, navigation and first-use expectations.
Core workflow
Practice the central workflow or certification scenario for this topic.
Troubleshooting
Review common issues, validation signals and safe operating practices.
Assessment prep
Use assignments, review prompts and Q&A to confirm readiness.
Data Engineering on Microsoft Azure Course is taught in the context of real delivery work.
You learn how the topic connects with engineering, operations, security, cloud, release or platform workflows.
Core foundations
Terminology, concepts, architecture and operating model.
Workflow traceability
Map practical work to tasks, approvals, documentation and delivery visibility.
Automation and integration
Use the topic with validation checks, automation hooks and delivery workflows.
Governance controls
Operate with permissions, approvals, policy checks and production-safe workflows.
How your practical work is assessed.
Your certificate is backed by labs, assignments, review and completion evidence.
Assignments
Assignments verify concepts, configuration, workflow quality and operating discipline.
Hands-on validation
Learners complete practical usage, implementation and troubleshooting exercises.
Completion record
Certificate issuance is tied to participation, practical completion and course coverage.
Completion record and certification support.
Learners receive DevOpsSchool completion support, course participation evidence and guidance aligned to the program objective. Certification-oriented pages also support exam readiness discussion.
Certificate verificationCertificate of Completion
Data Engineering on Microsoft Azure Course
Unique credential ID, verifiable online
Led by Rajesh Kumar and the DevOpsSchool practitioner network.
Training is grounded in practical DevOps, SRE, cloud, security, release and platform engineering experience.
What learners say about training with Rajesh Kumar.
“Rajesh is very good trainer. Rajesh was able to resolve our queries and question effectively. We really liked the hands-on examples covered during this training program.”
“Very well organized training, helped a lot to understand the AWS concept and detailed related to various tools. Very helpful”
“The training was very useful and interactive. Rajesh helped develop the confidence of all.”
Rated 4.6 on Google · All testimonials · Video reviews on YouTube
Quoted as published, from learners in Rajesh Kumar's live trainings across DevOpsSchool courses.
Why this DevOpsSchool program is different.
The value is not only one course page. The subscription unlocks the wider learning ecosystem for one year.
| Feature | DevOpsSchool | Typical short course |
|---|---|---|
| Access model | LMS access with 20+ courses and 50+ tools | Usually one course only |
| Live training | Demos, labs, Q&A and practical review | Often lecture-heavy |
| Corporate fit | Can align to roles, workflows and rollout goals | Limited customization |
| Certificate support | Completion record and readiness guidance | Varies by provider |
Questions learners usually ask before joining.
Is this course part of a level path?
Not always. Some courses focus on one topic, exam, product, role or service. They follow a focused agenda instead of Foundation to Advanced levels.
What is included in self-paced access?
One year of complete LMS access, 20+ additional courses and 50+ tools. Course families with multiple levels include available levels by default.
Can corporate teams customize this?
Yes. The program can be aligned to team roles, internal tools, delivery workflows and adoption goals.
How long is live training?
The Live & Interactive option is max 8 to 10 hours with demos, labs, Q&A and practical review.
Talk to DevOpsSchool before choosing the batch.
Use this support section for batch questions, corporate planning, LMS access clarifications, or guidance on whether this program fits your team.
India / Worldwide: +91 99057 40781
USA: +1 (469) 756-6329
Email: contact@DevOpsSchool.com
Chat on WhatsAppExtend the course with articles, explainers and workflow guidance.
Continue learning with supporting articles that connect this topic to DevOps, automation, governance and delivery workflows.
Training snapshots and certificate preview.
A look at the completion certificate and the course.
Certificate preview
See what course completion evidence looks like.
Focused training
Course visuals reinforce the subject area and learning context.
Live batch experience
Training supports live online, private team and workshop-style delivery.
Request Data Engineering on Microsoft Azure Course details.
Ask for syllabus, batch schedule, self-paced LMS access, live training options or corporate proposal.