Microsoft Azure Data Engineering Training

|| Microsoft Azure Data Engineering Online Training for Canada

The Microsoft Azure Data Engineering Online Course for Canada is to give professionals the fundamental knowledge and abilities needed to create and execute reliable data engineering solutions with Microsoft Azure. Azure Stream Analytics, Azure Databricks, Azure Synapse Analytics, and Azure Data Lake Storage Gen2 are just a few of the Azure services that are covered in this extensive Microsoft Azure Data Engineering certification online course in Canada. With an emphasis on cloud-based analytics, real-time data processing, and data engineering best practices, this course guarantees that participants have the know-how required for an Azure-based solution to be implemented successfully.

Throughout the course, students will have practical experience with key Azure capabilities like serverless SQL pools, real-time analytics with Azure Stream Analytics, and Apache Spark Pools in Azure Synapse. Important skills for protecting data workflows, guaranteeing compliance, and combining Azure Synapse Analytics for machine learning activities with Power BI for reporting are also covered in the program. These skills are essential for building high-performance, safe, and scalable data solutions that satisfy contemporary corporate needs in a cloud-based setting.

Participants will have a firm grasp of data engineering concepts and be able to create and implement data-driven solutions that offer business insights after completing this Microsoft Azure Data Engineering Online Training in Canada. Professionals who are new to data engineering or who want to improve their knowledge of Microsoft Azure's cloud technologies will find this course to be very beneficial. The Online Classes in Canada are designed to equip students with real-world, practical information that will help them succeed in the rapidly changing field of data engineering.

|| Choose Microsoft Azure Data Engineering Certification Training From BIT

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|| What will I learn?

Gain proficiency in building and managing data pipelines, data lakes, and data warehouses using Azure services.
Learn how to design and implement data storage solutions, data processing solutions, and data security solutions in Azure.
Develop skills in ensuring data security, privacy, and compliance in Azure data solutions.

Prepare for the DP-203 certification exam through hands-on labs and practice exams.
Understand the principles and components of data engineering on Microsoft Azure.
Explore data integration, transformation, and orchestration techniques in Azure.

|| What will I learn?

Gain proficiency in building and managing data pipelines, data lakes, and data warehouses using Azure services.
Learn how to design and implement data storage solutions, data processing solutions, and data security solutions in Azure.
Develop skills in ensuring data security, privacy, and compliance in Azure data solutions.
Prepare for the DP-203 certification exam through hands-on labs and practice exams.
Understand the principles and components of data engineering on Microsoft Azure.
Explore data integration, transformation, and orchestration techniques in Azure.

|| Requirements

Basic understanding of data engineering concepts and principles.

Familiarity with Microsoft Azure fundamentals and cloud computing concepts is beneficial.

|| Requirements

Basic understanding of data engineering concepts and principles.
Familiarity with Microsoft Azure fundamentals and cloud computing concepts is beneficial.

The DP-203: Data Engineering on Microsoft Azure certification course provides comprehensive training for professionals aiming to become proficient in designing and implementing data solutions on the Azure platform. The course covers essential topics such as data storage, processing, and security using Azure tools and services like Azure Synapse Analytics, Azure Data Lake Storage, Azure Data Factory, and Azure Stream Analytics. Participants learn to design and optimize data pipelines, implement data security practices, and monitor data solutions for performance and cost efficiency. By gaining expertise in these areas, professionals can effectively manage large-scale data workloads and provide valuable insights to their organizations. This certification not only validates an individual's technical skills but also enhances their career prospects by aligning their expertise with the growing demand for Azure data engineering solutions in the industry.

Introduction to Azure Data Services:
Overview of Azure data services and the Azure Data platform.
Understanding the benefits of cloud-based data solutions compared to on-premises alternatives.
Exploring different Azure data services including Azure Synapse Analytics, Azure Data Lake Storage, Azure Databricks, and Azure Data Factory.

Data Storage and Processing:
Provisioning and configuring Azure Storage accounts for different data types and workloads.
Implementing data ingestion and processing pipelines using Azure Data Factory.
Working with structured, semi-structured, and unstructured data formats.

Data Transformation and Analysis:
Performing data transformation and preparation tasks using Azure Data Factory Data Flows.
Exploring data analysis and visualization capabilities with Azure Synapse Analytics.
Implementing data exploration and machine learning experiments with Azure Databricks.

Big Data Processing and Analytics:
Setting up big data clusters in Azure Synapse Analytics for scalable data processing.
Implementing real-time data processing solutions using Azure Stream Analytics.
Building and deploying machine learning models with Azure Machine Learning.

Data Integration and Orchestration:
Implementing data integration solutions to connect disparate data sources and systems.
Orchestrating complex data workflows and dependencies using Azure Data Factory.
Integrating data from on-premises and cloud-based sources using Azure Hybrid Connections and Data Gateway.

Data Security and Governance:
Implementing data security and access control measures using Azure Active Directory.
Configuring data encryption, masking, and anonymization techniques to protect sensitive data.
Implementing data governance policies and compliance standards in Azure data solutions.

Data Monitoring and Optimization:
Monitoring data pipelines and workflows for performance, reliability, and scalability.
Implementing logging, telemetry, and alerting mechanisms using Azure Monitor.
Optimizing data storage and processing costs through resource management and utilization.

Data Storage and Archiving Strategies:
Implementing data storage and archiving strategies using Azure Blob Storage and Azure Data Lake Storage.
Configuring tiered storage and lifecycle management policies for efficient data management.
Implementing data retention and archival policies to comply with regulatory requirements.

Data Quality and Master Data Management:
Implementing data quality solutions to ensure data accuracy, completeness, and consistency.
Performing data cleansing, validation, and enrichment tasks using Azure Data Factory and Azure Databricks.
Implementing master data management (MDM) solutions to manage and govern organizational data assets.

Data Pipeline Automation and DevOps:
Implementing continuous integration and continuous deployment (CI/CD) pipelines for data solutions.
Automating data pipeline provisioning, deployment, and monitoring using Azure DevOps and Azure Resource Manager (ARM) templates.
Leveraging Infrastructure as Code (IaC) principles for managing and scaling data infrastructure.

Exercise 1: Setting Up Azure Data Lake Storage Gen2
Objective: Provision and configure Azure Data Lake Storage Gen2.
Create an Azure Data Lake Storage Gen2 account in your Azure subscription.
Configure access control settings using Azure AD integration.
Create file systems within the storage account for organizing data.
Upload sample data files (e.g., CSV, JSON) to the storage account.
Set up access control lists (ACLs) to manage permissions on files and directories.

Exercise 2: Implementing Data Ingestion with Azure Data Factory
Objective: Design and deploy a data ingestion pipeline using Azure Data Factory.
Set up linked services for connecting to the source and destination data stores (e.g., Azure Blob Storage, Azure SQL Database).
Define datasets to represent the source and destination data entities.
Create a pipeline with a Copy Data activity to ingest data from the source to the destination.
Configure data movement settings such as partitioning, compression, and concurrency.
Schedule the pipeline to run at regular intervals or trigger it based on specific events.
Monitor pipeline execution and track data ingestion progress using Azure Data Factory monitoring tools.

Exercise 3: Data Transformation with Azure Databricks
Objective: Perform data transformation tasks using Azure Databricks.
Create an Azure Databricks workspace in your Azure subscription.
Set up clusters with the appropriate configurations for data processing tasks.
Import sample data into Databricks workspace from Azure Data Lake Storage Gen2 or Blob Storage.
Implement data transformation logic using Spark DataFrame APIs or SQL queries.
Explore data visualization capabilities in Databricks notebooks.
Optimize data processing performance by tuning Spark configurations and cluster settings.

Exercise 4: Real-Time Data Processing with Azure Stream Analytics
Objective: Build and deploy a real-time data processing solution using Azure Stream Analytics.
Create an Azure Stream Analytics job in your Azure subscription.
Configure input sources to ingest streaming data from event hubs, IoT Hubs, or other streaming platforms.
Define stream analytics queries to perform real-time data transformation and analysis.
Configure output sinks to store or visualize the processed data (e.g., Azure Blob Storage, Azure SQL Database, Power BI).
Test the stream analytics job by sending sample data through the input sources.
Monitor job execution and troubleshoot any issues using Azure Stream Analytics monitoring tools.

Exercise 5: Building Data Pipelines with Azure Synapse Analytics
Objective: Design and deploy data pipelines using Azure Synapse Analytics.
Create an Azure Synapse Analytics workspace in your Azure subscription.
Define linked services to connect to various data sources and destinations.
Design data flow activities to orchestrate data movement and transformation tasks.
Implement data ingestion, transformation, and loading (ETL) logic using SQL scripts or Spark jobs.
Optimize data processing performance by leveraging distributed query processing and parallel execution.
Monitor pipeline execution and track data pipeline performance using Azure Synapse Analytics monitoring capabilities.

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|| Scope & Career Opportunities of Microsoft Azure Data Engineering in India

The future scope for professionals with the DP-203: Data Engineering on Microsoft Azure certification is highly promising. As data-driven decision-making becomes increasingly critical across industries, the demand for skilled data engineers continues to grow. The widespread adoption of cloud computing, particularly on Azure, amplifies this demand, providing ample opportunities for certified professionals to design, implement, and manage robust data solutions.

As organizations increasingly rely on cloud platforms, the need for skilled Azure data engineers has surged, with 95% of Fortune 500 firms leveraging Azure cloud services. The big data market is expanding rapidly, projected to reach $273.4 billion by 2026, which fuels demand for data experts, especially those proficient in Azure data engineering. The DP-203 certification opens doors to exciting roles such as data engineer, data analyst, or database administrator within the Azure ecosystem, and professionals who hold this certification often report job promotions and salary increments. Additionally, Microsoft certifications are recognized worldwide, making the DP-203 a valuable asset for career growth.

Additionally, as organizations leverage advanced analytics and AI, the expertise to handle large data volumes and implement sophisticated data processing pipelines becomes essential. Certified data engineers will play pivotal roles in various industries, including finance, healthcare, and retail, ensuring data governance and compliance with evolving regulatory requirements. This certification not only enhances career growth and salary prospects but also opens doors to advanced positions such as Senior Data Engineer and Data Architect. Moreover, the integration with other Microsoft technologies and the continuous evolution of big data tools and frameworks mean that certified professionals will remain at the forefront of innovation, making significant contributions to their organizations' strategic goals and maintaining a competitive edge in the tech industry.

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|| Average Annual Salary of Professionals with Microsoft Azure Data Engineering

The average salary of professionals with a DP-203: Data Engineering on Microsoft Azure certification in India varies based on experience, location, and specific role. Typically, the annual salary for an Azure Data Engineer in India ranges between ₹4.0 Lakhs to ₹15.0 Lakhs, with an average of ₹8.2 Lakhs. This certification enables professionals to work with Azure data services, integrate data from various sources, and design analytics solutions. Salaries can vary significantly depending on the company, city, and the individual's skill set. Cities like Bangalore, Mumbai, and Delhi often offer higher salaries due to the concentration of tech companies and higher cost of living.

In the United States, the salary range for an Azure Data Engineer is from $111,491 to $138,695 per year, with an average base salary of $126,015. Experienced professionals can earn up to $156,863 annually, particularly in high-paying cities such as San Jose, Santa Clara, and Fremont in California.

|| Data Engineering on Microsoft Azure certification hold a prominent position in India job market

The DP-203: Data Engineering on Microsoft Azure certification opens up numerous placement opportunities in India across various industries, reflecting the increasing demand for data engineering skills. Certified professionals can find roles in leading IT companies, startups, and multinational corporations that require expertise in managing, transforming, and optimizing data. Positions such as Data Engineer, Azure Data Engineer, Data Analyst, and Cloud Data Architect are highly sought after, with responsibilities that include designing and implementing data solutions, managing data workflows, and optimizing data storage and processing on the Azure platform. Industries such as finance, healthcare, e-commerce, and telecommunications particularly value these skills for their data-driven decision-making processes and cloud-based infrastructure needs. Additionally, consulting firms and service providers look for certified experts to help clients migrate to and optimize their operations on Microsoft Azure. With the rapid adoption of cloud technologies in India, the DP-203 certification significantly enhances career prospects, offering opportunities for growth, attractive salaries, and the potential for impactful work in data engineering and cloud computing.

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|| Top Companies Hiring for DP-203: Data Engineering on Microsoft Azure Certified Professionals

Professionals with DP-203: Data Engineering on Microsoft Azure certification are highly sought after by top companies globally. In India, leading IT firms like Tata Consultancy Services (TCS), Infosys, and Wipro are prominent recruiters for Azure-certified roles. Multinational corporations such as Accenture and Capgemini also offer opportunities. Globally, companies like Microsoft, Amazon Web Services (AWS), Google Cloud Platform (GCP), IBM, and Deloitte actively hire Azure-certified professionals for data engineering roles. These companies recognize the value of Azure certification and actively seek professionals to build and manage their data solutions on the Azure platform.

|| Top Hiring Companies

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|| Get Microsoft Azure Data Engineering Certification Training

Three easy steps will unlock your Microsoft Azure Data Engineering Certification:

Finish the online / offline course of Microsoft Azure Data Engineering Course and the Assignment
Take on and successfully complete a number of industry-based Projects
Pass the Microsoft Azure Data Engineering Certification exam

The certificate for this Microsoft Azure Data Engineering Certification will be sent to you through our learning management system, where you can also download it. Add a link to your certificate to your CV or LinkedIn profile.

Microsoft Azure Data Engineering Training in Canada

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|| Microsoft Azure Data Engineering Online Training for Canada

|| Choose Microsoft Azure Data Engineering Certification Training From BIT

|| What will I learn?

|| What will I learn?

|| Requirements

|| Requirements

Microsoft Azure Data Engineering Course Content

Data Engineering on Microsoft Azure Certification Lectures

Data Engineering on Microsoft Azure Lab

Get in touch

|| Scope & Career Opportunities of Microsoft Azure Data Engineering in India

|| From Learning to Earning with BIT

|| Average Annual Salary of Professionals with Microsoft Azure Data Engineering

|| Data Engineering on Microsoft Azure certification hold a prominent position in India job market

|| Empowering Your Career Transition From Learning To Leading

Manu Modi

Dhruvi Parmar

Priya Gamit

Nayan Pathan

Naresh Patel

|| Top Companies Hiring for DP-203: Data Engineering on Microsoft Azure Certified Professionals

|| Top Hiring Companies

|| Get Microsoft Azure Data Engineering Certification Training

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