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Azure Data Engineering Training in Gurgaon
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Data Engineering
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Gurgaon
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About Course
Master Azure Data Engineering Training in Gurgaon with hands-on training in Azure Data Factory, Synapse, Databricks & more. Learn from experts at ProCode Technologies.
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What I will learn?
Zero-Cost Internship Programs
Goal Oriented Work Experience Projects
Industry-Focused Trainers for Constant Learning
Support for Job Hunting after Completing the Course
Courses Offered at Reasonable Rates and Free Certification
Suitable for Students and Employed People Alike
Course Curriculum
Introduction to Azure Data Engineering
Understanding the role and responsibilities of a Data Engineer
Overview of data engineering processes and workflows
Importance of data engineering in modern data-driven organizations
Introduction to Microsoft Azure’s data services and tools
Azure Fundamentals
Overview of Microsoft Azure architecture and services
Navigating the Azure Portal and understanding resource management
Creating and managing Azure resources and subscriptions
Understanding Azure regions, availability zones, and resource groups
Azure Storage Solutions
Introduction to Azure Storage Accounts and their types
Working with Azure Blob Storage, Table Storage, and Queue Storage
Implementing security measures and access controls in storage accounts
Managing data redundancy and replication strategies
Azure Data Lake Storage Gen2
Understanding the features and benefits of Data Lake Storage Gen2
Setting up and configuring Data Lake Storage for big data analytics
Managing hierarchical namespaces and access control lists (ACLs)
Integrating Data Lake Storage with other Azure services
Azure SQL Database and Azure Synapse Analytics
Exploring Azure SQL Database and its deployment models
Introduction to Azure Synapse Analytics and its components
Designing and implementing data warehouses using Synapse Analytics
Querying and analyzing data using Synapse SQL pools
Azure Data Factory (ADF)
Understanding the architecture and components of Azure Data Factory
Creating and managing pipelines for data movement and transformation
Implementing data flows and mapping data transformations
Monitoring and troubleshooting data pipelines
Azure Databricks
Introduction to Azure Databricks and its integration with Azure services
Working with Apache Spark for big data processing
Developing notebooks for data exploration and transformation
Implementing machine learning models using Databrick
Real-Time Data Processing with Azure Stream Analytics
Designing and implementing data integration solutions using Azure services
Orchestrating complex data workflows with Azure Data Factory
Managing dependencies and scheduling data pipelines
Implementing error handling and retry mechanisms
Data Integration and Orchestration
Designing and implementing data integration solutions using Azure services
Orchestrating complex data workflows with Azure Data Factory
Managing dependencies and scheduling data pipelines
Implementing error handling and retry mechanisms
Capstone Project
Applying acquired knowledge to a real-world data engineering project
Designing and implementing an end-to-end data pipeline
Presenting project outcomes and receiving feedback
Preparing for certification exams and job interviews
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A course by
TA
Thameem Ahamad
Requirements
Enhances collaboration between data engineers, analysts, and operations teams.
Speeds up data pipeline development and deployment cycles.
Improves data quality and consistency through automated testing.
Enables continuous integration and delivery in data workflows.
Reduces operational costs with efficient data management practices.
Increases agility in handling dynamic business data requirements.
Tags
Target Audience
Enables the creation of scalable and efficient data pipelines.
Facilitates real-time and batch data processing for analytics.
Integrates structured and unstructured data from multiple sources.
Supports data warehousing and large-scale storage solutions.
Ensures data quality, consistency, and reliability across systems.
Powers business intelligence and machine learning applications.
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