Azure Data Engineering

4.5
4.5/5

Learn the skills you need to become an Azure Data Engineering expert and quickly transform your career.

4.5

4.3

4.8

Azure Data Engineering

Fees at  Azure Data Engineering  
20,000

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+91 91769 04546

4.5

4.5

4.5

Azure Data Engineering

Data Integration Powerhouse: Azure Data Factory is Microsoft’s fully managed data integration service that orchestrates and automates data movement and transformation across various data sources and destinations in the cloud and on-premises.

Versatility Across Ecosystems: It seamlessly integrates with diverse data stores such as Azure Blob Storage, Azure Data Lake Storage, Azure SQL Database, and many others, enabling unified data access and processing.

Workflow Orchestration: ADF empowers data engineers to create, schedule, and monitor data pipelines with ease. It supports a graphical interface for building workflows that include data ingestion, transformation, and loading tasks

Scalability and Reliability: Built on Azure’s robust infrastructure, ADF handles data pipelines of any scale, ensuring high availability, fault tolerance, and scalability as data volumes grow.

Integration with Azure Ecosystem: It integrates deeply with other Azure services like Azure Databricks for advanced analytics, Azure Synapse Analytics (formerly SQL Data Warehouse) for data warehousing, and Azure DevOps for continuous integration and deployment (CI/CD) of data pipelines.

Course Includes

Request for more information

Beems Azure Data Engineering training offers you a piece of in-depth knowledge.

Azure Data Engineering Industry-Oriented Course Curriculum

 Industry-focused curriculum for career advancement.

  • Types of Cloud and Cloud Services
  • Overview of Azure Portal and Various Services
  • Azure Storage Services
  • Azure Accounts: Subscription, Resources, and Management
  • Blob Storage and Azure SQL Server Introduction
  • Evolution of Storage Solutions in Azure
  • Azure Data Lake vs Blob Storage
  • Introduction to Data Processing
  • Azure Data Factory (ADF) Introduction and Importance
  • ADF Architecture Overview
  • Data Factory Components and Concepts
  • Working Principles of ADF
  • Steps to Create an Azure Data Factory
  • Integration Runtime in ADF
  • DataSets and LinkedServices in ADF
  • Triggers in ADF
  • ARM Templates for ADF Deployment
  • Linked Services Authorization and Security
  • Creating Linked Services and Datasets in ADF
  • Parameters and Variables in ADF
  • Data Movement Activities in ADF
  • Control Flow Activities in ADF
  • Creating and Managing Pipelines in ADF
  • Scenarios for Data Copy and Movement in ADF
  • Moving Files from Azure Data Lake to Azure SQL Server
  • Overview and Importance of Azure Data Lake
  • Azure Data Lake Storage Gen2 vs Gen1
  • Data Ingestion Strategies into Azure Data Lake
  • Security and Access Control in Azure Data Lake
  • ADF Mapping Data Flows vs Azure Databricks
  • Integrating ADF with Azure Databricks
  • Exploring Azure Databricks and Spark Basics
  • Understanding Spark Architecture and Components
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  • Azure Databricks Workspace Exploration
  • Managing Clusters, Cluster Pools, and Runtimes
  • Creating and Configuring Databricks Clusters
  • DataBricks File System (DBFS)
  • Notebook Creation, Management, and Manipulation in ADB
  • Mounting Azure Data Lake Storage in ADB
  • RDD, DataFrame, and Datasets in Spark
  • Lazy Evaluation in Spark
  • Working with DataFrames: Creating and Transforming
  • Introduction to PySpark and its API Functions
  • Introduction to Delta Lake and its Benefits
  • Slowly Changing Dimensions (SCD) and Types
  • Understanding Fact & Dimensions Tables
  • Overview of Various File Formats: Parquet & Avro
  • Shuffle Operations and Partitioning Strategies
  • Narrow vs Wide Transformation in Spark
  • Transformation Techniques using Data Frame API Methods
  • Comparing PySpark and Pandas DataFrame
  • Integrating PySpark with Pandas and vice versa
  • Implementing User-Defined Functions (UDFs) in PySpark
  • Analytic Functions and Techniques in PySpark
  • Optimizing Slowly Changing Dimensions (SCD) in Spark
  • Strategies for Scheduling and Monitoring Notebooks in ADB
  • Introduction to Azure DevOps
  • Exploring Git: Branching, Merging, and Best Practices
  • CI/CD Pipelines with Azure Data Factory (ADF) and Azure Databricks (ADB)
  • End-to-End Workflows in Azure Synapse Analytics
  • Layers of Data Handling in Azure Synapse Analytics
  • Overview of Azure Monitor and its Capabilities
  • Data Collected by Azure Monitor
  • Monitoring Azure Data Engineering Workloads
  • Alerts and Notifications in Azure
  • What is Azure Batch?
  • Intrinsically Parallel Workloads
  • Additional Batch Capabilities
  • Working of Azure Batch
  • Scalability and Performance Tuning Tips
  • Design Patterns for Efficient Data Engineering in Azure
  • Cost Management Strategies in Azure Data Engineering
  • Disaster Recovery and High Availability Planning

Our Instructor

Name

Srinivasan

Experience

20+ Years

Specialized in

Data Engineering, Cloud Architect.

More Details

Welcome to Azure Data Factory, your gateway to mastering data integration and orchestration in the cloud!
 
I’m Srini,
            I’m excited to guide you through this transformative journey in data engineering with Microsoft’s powerful tool, Azure Data Factory.
 

           As your trainer, I bring years of hands-on experience in deploying data solutions across various industries. Azure Data Factory isn’t just another tool—it’s a game-changer in how we manage, process, and deliver data at scale. Whether you’re new to data engineering or looking to enhance your skills, this training will equip you with the knowledge and practical insights to excel in today’s data-driven world.

            In our sessions, we’ll delve into ADF’s capabilities to seamlessly integrate data from diverse sources such as Azure Blob Storage, SQL Database, and beyond. You’ll learn to design and automate complex data pipelines, optimize performance with advanced transformations, and ensure data reliability and scalability with Azure’s robust infrastructure.

           Moreover, we’ll explore ADF’s integration with Azure Synapse Analytics and Azure Databricks, empowering you to leverage powerful analytics and machine learning capabilities directly within your data workflows.

           By the end of this training, you’ll not only understand the intricacies of ADF but also gain the confidence to architect and deploy end-to-end data solutions that meet enterprise demands. Get ready to unlock the full potential of Azure Data Factory and embark on a journey towards becoming a proficient data engineer in the Azure ecosystem.

           Let’s dive in and elevate your data engineering skills with Azure Data Factory!

Azure Data Engineering Detailed Demo

Azure Data Engineering Course Reviews

Students praise practical learning and expert trainers.

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Azure Data Engineering training at Beems Technologies transformed my career. Real-time trainers made complex concepts easy to grasp.
Nandhini
1571
The hands-on approach in Azure Data Engineering training helped me gain practical skills. Highly recommend Beems Technologies
Surya
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Beems Technologies' Azure Data Engineering training exceeded my expectations. The trainers' industry insights were invaluable
Hari
2889
Thanks to Beems Technologies, I landed my dream job after completing Azure Data Engineering. Top-notch support and guidance!
Nasar
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Beems Technologies' Azure Data Engineering training boosted my confidence and skills. Practical exercises and personalized attention made all the difference.
Ananthy
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