Azure Data Engineering: The Driving Force of Modern Data Analytics
100% Placement Assistance
The Azure Data Engineering program equips you with the skills to design and manage data pipelines using Microsoft Azure and big data technologies. This all-inclusive training covers vital concepts such as ETL processes, data transformation, automation, and cloud-native data solutions. You’ll gain hands-on experience with tools like Azure Data Factory, Databricks, and Synapse Analytics, while mastering best practices for data modeling, pipeline optimization, and large-scale data processing. With real-world projects and practical experience, this program prepares you for a successful career in Azure Data Engineering.
Take The First Step To Your Goals
Course Overview
The Azure Data Engineering Training Program empowers professionals to excel in the field of data engineering using Microsoft Azure. Through hands-on projects and expert-led instruction, participants gain proficiency in data integration, ETL processes, and cloud-based data solutions. This program prepares participants for the job market with practical labs, real-world scenarios, and interview coaching, equipping them for success in Azure data engineering roles.
Distinctive Advantages
- E-Learning Opportunities
- Seasoned Professional Trainers
- Hands-On Project Experience
- Always-On Practical Live Assistance
- Professional Resume Writing
- Interactive Learning Sessions
- Expert-Led Workshops
- Access Training Anywhere
- Interview Preparation
- Soft Skill Enhancement
- Corporate Culture Orientation
- Placement Assistance
- Alumni Support Network
- Job Market Insights
Crafted by Industry Specialists, this curriculum emphasizes practical learning through real-world case studies, allowing students to gain hands-on experience.
It’s not just learning – it’s an immersive and transformative experience.
- Introduction to Azure Data Engineering
- Data Storage Options in Azure
- Azure Data Factory (ADF
- Data Ingestion & Transformation
- Working with Azure Synapse Analytics
- Data Security & Compliance
- Real-time Data Processing
- Data Governance and Monitoring
- Advanced Analytics with Power BI & Azure
- Capstone Project
- Career Development and Networking
- Interview Preparation & Resume Building
Program Overview: Shaping Modern Data Solutions with Azure Data Engineering
Module 1: Introduction to Azure Data Engineering
- Overview of Azure services
- Role and responsibilities of a data engineer
- Key concepts in cloud computing
- Introduction to Azure portal, subscriptions, and resources
Module 2: Data Storage Options in Azure
- Azure Storage: Blob, Table, Queue, and Files
- Azure Data Lake Storage (ADLS): Features and use cases
- Azure SQL Database: Key features and deployment
- Cosmos DB: NoSQL database options
- Storage security best practices
Module 3: Azure Data Factory (ADF)
- Introduction to ADF and data orchestration
- Creating and scheduling pipelines
- Data movement and transformation activities
- Integration with on-premise and cloud sources
- Monitoring and optimizing ADF pipelines
Module 4: Data Ingestion & Transformation
- Azure Databricks: Fundamentals and workspace setup
- Data ingestion with Apache Spark on Databricks
- Transformations using PySpark and Databricks SQL
- Managing and optimizing big data pipelines
Module 5: Working with Azure Synapse Analytics
- Introduction to Synapse Analytics and key features
- Synapse Studio: Managing data, notebooks, and pipelines
- Data integration with Synapse Pipelines
- Big data and machine learning integration
- Monitoring performance and costs
Module 6: Data Security & Compliance
- Encryption, Authentication, and Authorization
- Managing security in data storage services (Blob, SQL DB, etc.)
- Implementing Azure RBAC (Role-Based Access Control)
- Managing compliance in data storage and movement
Module 7: Real-time Data Processing with Stream Analytics
- Introduction to real-time data streaming
- Configuring Azure Stream Analytics jobs
- Integration with Event Hubs, IoT Hub, and Kafka
- Querying streaming data with Query language
- Real-time dashboards and Alerting
Module 8: : Data Governance and Monitoring
- Introduction to Azure Purview: Data cataloging and lineage
- Data Monitoring and Logging
- Troubleshooting performance issues
- Monitoring data quality and governance standards
Module 9: Advanced Analytics with Power BI & Azure
- Connecting Power BI to Azure data sources
- Building and optimizing reports and dashboards
- Real-time data visualization
- Embedding Power BI reports in Azure applications
Module 10: Capstone Project
- End-to-end data pipeline implementation
- Real-time data streaming solutions
- Integrating multiple Azure services in a single project
- Data security and compliance in a live scenario
- Performance optimization and monitoring tasks
Module 11: Soft Skills Training, Interview Preparation, & Professional Resume Building
Soft Skills Training
- Communication skills for Data Engineers
- Collaboration in cross-functional teams
- Problem-solving and critical thinking
Interview Preparation
- Common interview questions for Data Engineering roles
- Behavioural interview techniques
- Mock interviews and feedback sessions
Professional Resume Building
- Crafting a resume tailored to Data Engineering roles
- Highlighting technical skills and project experience
- LinkedIn profile optimization and online presence
Industry Insight : The Growing Importance of Azure Data Engineering Skills in Today's Workforce
Recent industry analyses indicate that Azure Data Engineering skills are witnessing significant demand, especially in data-centric roles. Azure Data Engineers are essential for designing, implementing, and managing scalable data solutions on the Azure platform. As businesses continue to prioritize data-driven decision-making, professionals with expertise in Azure Data Engineering are increasingly sought after. These specialists can expect competitive salaries averaging between INR 10 L to 15 L per year, reflecting their ability to handle complex data architectures and contribute to effective business strategies across various sectors.
Eligibility Criteria
With the rising demand for Azure Data Engineering, professionals from diverse sectors are actively pursuing training in this field. This course is perfect for those looking to enhance their careers in Data Engineering, Analytics, and Cloud technology. Fresh Graduates, College Students, Data Analysts, Business Intelligence experts, and IT professionals seeking to specialize in Azure-based data solutions will find this training especially advantageous.
Essential Background
No prior experience in Azure Data Engineering is required to enroll in this course, although a basic grasp of cloud computing concepts and data management can be beneficial. Achieving proficiency in Azure Data Engineering demands dedication and effort, but the course is structured to simplify the complexities of the platform and its applications. With the right commitment and diligence, you can develop expertise in Azure and elevate your data engineering skills. Consider signing up for this Azure Data Engineering course to gain a competitive advantage in the rapidly changing data landscape.
- Seasoned Industry Expert: More than 10 years of experience in Azure Data Engineering, ETL, and Data Analysis.
- Proven Track Record: Extensive background in delivering successful data solutions across various industries.
- Hands-On Experience: Expertise in managing and optimizing large-scale data environments and ETL processes.
- Educational Background: Strong academic foundation with relevant degrees and certifications
- Advanced Skill Set: Proficient in a wide range of data engineering tools and technologies.
- Industry Leadership: Recognized leader in data engineering with a history of impactful contributions to the field.
- Practical Insights: Provides real-world case studies and practical examples from a decade of experience.
- Innovative Approach: Known for applying cutting-edge techniques and best practices in data management.
- Professional Achievements: Successfully led numerous high-profile projects and data transformation initiatives.
- Mentorship Skills: Committed to guiding and mentoring students to achieve their career goals.
- Global Perspective: Experience working with international teams and projects, bringing a global viewpoint.
- Technical Proficiency: In-depth knowledge of data engineering, ETL processes, and analytical tools.
- Effective Communication: Excellent ability to convey complex concepts in an understandable and engaging manner.
- Continuous Learning: Dedicated to staying updated with the latest industry trends and technologies
- Client Success Stories: Demonstrated success in delivering impactful data solutions for a range of clients.
- Customized Training: Skilled in tailoring training programs to meet the specific needs of diverse audiences.