Best Software Training Institute in Hyderabad – Version IT

Azure Data Engineer Training in Vijayawada

  • Train to Get Certified through the top Azure Data Engineer online Training in Vijayawada.
  • Be trained by Experts with over 15 years of experience.
  • 100+ real-time projects.

⭐ 4.9/5 Rating

Based on 6,000+ student reviews

🎓 10,000+ Enrolled

Students worldwide

👨‍🏫 10+ Years Experience

Industry expert trainers

⭐ 4.9/5 Rating

Based on 6,000+ student reviews

📅 Course Duration

5 Months

💰 Course Price

₹ 30000

📄 Course Content

Overview of Azure Data Engineer Course in Vijayawada

 Learn Azure Data Engineer Course with one of the best institutes like Version IT in Vijayawada. The course is set in such a way that it fulfills the needs of the students and working professionals of all levels. From Microsoft, there is the global network of data centers, which is being motivated to produce Azure, since Microsoft Azure is a cloud computing platform to administer the services and applications, to deploy building and testing. The idea is based on a primary agenda of serving its users anytime, anywhere.

Employment Opportunities after Completing Azure Data Engineer Online Training in Vijayawada

After completing Azure Data Engineer Online Training at Vijayawada, there are numerous employment opportunities, which have been offered to individuals who want to pursue a career in cloud computing. Azure is a trending cloud platform that is deployed across businesses of any size, and businesses also require qualified professionals in Azure. Armed with the appropriate skills and experience, an Azure administrator, engineer or a developer can be hired. One can also choose to work in the Azure support or sales where the opportunities are numerous. You can become:

  • Azure Cloud Architect
  • Cloud Administrator
  • Cloud Developer
  • Cloud Networks Specialist
  • Azure Big Data Specialist

Why Choose Version IT for Azure Data Engineering Courses in Vijayawada?

 One of the best in terms of offering the Azure data engineering online training in Vijayawada is Version IT.

We also have a pool of qualified and skilled trainers willing to train you on how to use Azure and its different features. We also offer tailor-made training models in response to the unique requirements of our customers.

Key Features:

Live Labs On-The-Job Learning

Practice labs enables you to easily practice what you have learned in a secure setting that you can access anytime as long as you have a compatible PC, Browser and Internet connection.

Live Project Training

We provide live projects and the possibility to participate in project design with the aid of the partners in the industry such as business and community organizations.

Classroom Training

We shall apply the collaborative web conferencing alongside screen sharing to teach live online with high interactions.

24/7 Support

Got queries? We have our 24/7 support team who would go an extra mile in order to make your experience on Slack a communication platform an easy and enjoyable one.

Job & Interview Assistance

Our interview service will make you eliminate those fears and enter the next interview confidently and get your dream Job.

Internship after Course

Industry requires the finest talent to survive and flourish in the current dynamic and rapid world, you will have an opportunity to do Internships and working hand in hand that can be a major win to the Industry and the students/trainees.

Azure Data Engineering Courses Curriculum

All the topics that will be covered in Azure Data Engineer Course include:

  • Microsoft Azure Data Engineering Overview
  • Virtual Network Implementation and management.
  • Implement Virtual Machines
  • Managing Virtual Machines
  • Implementing Websites
  • Storage Planning and Implementing.
  • Adopting Mobile Services and Cloud Services.

Topics You will Learn

Cloud Computing Concepts
  • What is the “Cloud”?
  • Why cloud services
  • Types of cloud models
    • Deployment Models
    • Private Cloud deployment model
    • Public Cloud deployment model
    • Hybrid cloud deployment model
  • Types of cloud services
  • Infrastructure as a Service
  • Platform as a Service
  • Software as a Service
  • Comparing Cloud Platforms
    • Microsoft Azure
    • Amazon Web Services
    • Google Cloud Platform
  • Characteristics of cloud computing
    • On-demand self-service
    • Broad network access
    • Multi-tenancy and resource pooling
    • Rapid elasticity and scalability
    • Measured service
  • Cloud Data Warehouse Architecture
  • Shared Memory architecture
  • Shared Disk architecture
  • Shared Nothing architecture
Core Azure services
  • Securing network connectivity
  • Core Azure identity services
  • Security tools and features
  • Azure Governance methodologies
  • Monitoring and reporting
  • Privacy, compliance, and data protection standards
Azure Pricing and Support
  • bytes Data Type
  • byte array
  • String Formatting in Python
  • Math, Random, Secrets Modules
  • Introduction
  • Initialization of variables
  • Local variables
  • Global variables
Azure SQL Database
  • Introduction Azure SQL Database.
  • Comparing Single Database
  • Managed Instance
  • Creating and Using SQL Server
  • Creating SQL Database Services
  • Azure SQL Database Tools
  • Migrating on premise database to SQL Azure
  • Purchasing Models
  • DTU service tiers
  • vCore based Model
  • Serverless compute tier
  • Service Tiers
    • General purpose / Standard
    • Business Critical / Premium
    • Hyperscale
  • Deployment of an Azure SQL Database
  • Elastic Pools
  • What is SQL elastic pools
    • Choosing the correct pool size
  • Creating a New Pool
  • Manage Pools
  • Monitoring and Tuning Azure SQL Database
  • Configure SQL Database Auditing
  • Export and Import of Database
  • Automated Backup
  • Point in Time Restore
  • Restore deleted databases
  • Long-term backup retention
  • Active Geo Replication
  • Auto Failover Group
Azure Data Lake
  • Introduction to Azure Data Lake
  • What is Data Lake?
  • What is Azure Data Lake?
  • Data Lake Architecture?
  • Working with Azure Data Lake
  • Provisioning Azure Data Lake.
  • Explore Data Lake Analytics
  • Explore Data Lake Store
  • Uploading Sample File
  • Using Azure Portal
  • Using Storage Explorer
  • Using Azure CLI
Azure Data Factory
  • What is Data Factory?
  • Data Factory Key Components
  • Pipeline and Activity
  • Linked Service o Data Set
  • Integration Runtime Provision Required Azure Resources
  • Create Resource Group
  • Create Storage Account
  • Provision SQL Server and Create Database
  • Provision Data Factory
Practical Scenarios and Use Cases
  • ADF Introduction
  • Important Concepts in ADF
  • Create Azure Free Account for ADF
  • Integration Runtime and Types
  • Integration runtime in ADF-Azure IR
  • Create Your First ADF
  • Create Your First Pipeline in ADF
  • Azure Storage Account Integration with ADF
  • Copy multiple files from blob to blob
  • Filter activity __ Dynamic Copy Activity
  • Get File Names from Folder Dynamically
  • Deep dive into Copy Activity in ADF
  • Copy Activity Behavior in ADF
  • Copy Activity Performance Tuning in ADF
  • Validation in ADF
  • Get Count of files from folder in ADF
  • Validate copied data between source and sink in ADF
  • Azure SQL Database integration with ADF
  • Azure SQL Databases – Introduction Relational databases
  • Creating Your First Azure SQL Database
    • Deployment Models
    • Purchasing Modes
  • Overwrite and Append Modes in Copy Activity
  • Full Load in ADF
  • Copy Data from Azure SQL Database to BLOB in ADF
  • Copy multiple tables in Bulk with Lookup & ForEach in Data Factory
  • Logging and Notification Azure Logic Apps
  • Log Pipeline Executions to SQL Table using ADF
  • Custom Email Notifications Send Error notification with logic app
  • Use Foreach loop activity to copy multiple Tables- Step by Step Explanation
  • Incremental Load in ADF
  • Incremental Load or Delta load from SQL to Blob Storage in ADF
  • Multi Table Incremental Load or Delta load from SQL to Blob Storage
  • Incrementally copy new and changed files based on Last Modified Date
  • Azure Key Vault integration with ADF
  • Azure Key Vault, Secure secrets, keys & certificates in Azure Data
  • ADF Triggers:
  • Event Based Trigger in ADF
  • Tumbling window trigger dependency & parameters
  • Schedule Trigger
  • Self Hosted Integration Runtime
  • Copying On Premise data using Azure Self Hosted integration Runtime
  • Data Migration from On premise SQL Server to cloud using ADF
  • Load data from on premise sql server to Azure SQL DB
  • Data Migration with polybase and Bulk insert
  • Copy Data from sql server to Azure SQL DW with polybase & Bulk Insert
  • Data Migration from On premise File System to cloud using ADF
  • Copy Data from on-premise File System to ADLS Gen2
  • ToCopying data from REST API using ADF
  • Loop through REST API copy data TO ADLS Gen2-Linked Service Parameters
  • AWS S3 integration with ADF
  • Migrate Data from AWS S3 Buckets to ADLS Gen2
  • Activities in ADF
  • Switch Activity-Move and delete data
  • Until Activity-Parameters & Variables
  • Copy Recent Files From Blob input to Blob Output folder without LPV
  • Snowflake integration with ADF
  • Copy data from Snowflake to ADLS Gen2
  • Copy data from ADLS Gen2 to Snowflake
  • Azure CosmosDB integration with ADF
  • Copy data from Azure SQLDB to CosmosDB
  • Copy data from blob to cosmosDB
  • Advanced Concepts in ADF
  • Nested ForEach -pass parameters from Master to child pipeline
  • High Availability of Self Hosted IR &Sharing IR with other ADF
  • Data Flows Introduction
  • Azure Data Flows Introduction
  • Setup Integration Runtime for Data Flows
  • Basics of SQL Joins for Azure Data Flows
  • Joins in Data Flows
  • Aggregations and Derive Column Transformations
  • Joins in Azure DataFlows
  • Advanced Join Transformations with filter and Conditional Split
  • Data Flows – Data processing use case1
  • Restart data processing from failure
  • Remove Duplicate Rows &Store Summary Credit Stats
  • Difference Between Join vs.Lookup Transformation & Merge Functionality
  • Dimensions in Data Flows
  • Slowly Changing Dimension Type1 (SCD1) with HashKey Function
  • Flatten Transformation
  • Rank, Dense_Rank Transformatios
  • Data Flows Performance Metrics and Data Flow Parameters
  • How to use pivot and unpivot Transformations
  • Data Quality Checks and Logging using Data Flows
  • Batch Account Integration with ADF
  • Custom Activity in ADF
  • Azure Functions Integration with ADF
  • Azure HDInsight Integration with ADF
  • Azure HDInsight with Spark Cluster
  • Azure Databricks Integration with ADF
  • ADF Integration with Azure Databricks
  • Azure Data Lake Analytics integration with ADF

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FAQ's

Our training centers are all day on the working days and the training centers have our state-of-the-art lab infrastructure which you can use anywhere you want. In the case of online students, our servers and the lab facilities are available around the clock via the internet.

In the case of the classroom, you are allowed to attend the same session with another batch. In the case of Azure Data Engineer Online Training, each session is taped and you can watch at your own convenience and you may get to watch what was not covered.

Our trainers are all real time industry experts and with minimum experience of 10+ years. You can meet our instructors and check their profile before you enroll.

Our three flexible options are instructor-based classroom training, live instructor-based online training and self-paced video training.

Yes, we give group enrollment discounts and will organize tailor-made corporate training to your group. You can know more by contacting us.

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