About AZURE Data Engineer
Faculty Profile
Course Syllabus

The Data Science course offered by Version IT Hyderabad is the most comprehensive available in the market. The course covers a wide range of topics in data science.

Version IT is one of the top software training institutes in Hyderabad and the Academy can be chosen to accelerate your career with data science certification. Azure Data Engineer course is a perfect blend of theory, case studies and capstone projects. The course curriculum designed by Version IT is considered to be the best in the industry. With proud, we can say that you will get noticed by recruiters across the globe with the Version IT certification. 

A data engineer is responsible for preparing data for analytical or operational uses. The data engineer usually works with the analytics team, providing data in a ready-to-use form to data scientists who are looking to run queries and algorithms against the information for predictive analytics, machine learning and data mining purposes.

The Data Science course offered by Version IT Hyderabad is the most comprehensive Data Science course available in the market. The course covers the complete Data Science lifecycle concepts from Data Collection, Data Extraction, Data Cleansing, Data Exploration, Data Transformation, Feature Engineering, Data Integration, Data Mining, building Prediction models, Data Visualization and deploying the solution to the customer. Skills and tools ranging from Statistical Analysis, Text Mining, Regression Modelling, Hypothesis Testing, Predictive Analytics, Machine Learning, Deep Learning, Neural Networks, Natural Language Processing, Predictive Modelling, R Studio, Tableau, Spark, Hadoop, programming languages like R programming, Python are covered extensively as part of this Data Science training. 

Version IT is considered the best Data Science training institute in Hyderabad. We offer services from training to placement. Our students have been placed in various multinational companies including. Version IT is imparting the best Data Science training in Hyderabad and it has acclaimed as the best academy in the industry. 

A galore of opportunities

  • A report by NASSCOM revealed that about 1.4 Lakh jobs are vacant in Data Science, Artificial Intelligence and Big Data roles
  • The world will notice a deficit of 2.3 Lakh Data Science professionals by 2022
  • The demand for Data Scientist professionals has been increasing every year
  • Data Science is the best job to pursue according to Glassdoor rankings
  • Harvard Business Review mentioned that ‘Data Scientist is the sexiest job of the 21st century’

Sri Ram Sr.Consultant

SRI RAM is a versatile mentor having Through knowledge in Azure Data Engineer. With his vast Experience he served in top most MNC's .With his unique teaching methods sriram trained hundreds of students and professionals in Azure.He Guided many aspirants by assisting them to get the job Opportunities.

Module 1: 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

Module 2: Core Azure services

  • Core Azure Architectural components
  • Core Azure Services and Products
  • Azure solutions
  • Azure management tools

Module 3: Security, Privacy, Compliance

  • Securing network connectivity
  • Core Azure identity services
  • Security tools and features
  • Azure Governance methodologies
  • Monitoring and reporting
  • Privacy, compliance, and data protection standards

Module 4: Azure Pricing and Support

  • Azure subscriptions
  • Planning and managing costs
  • Azure support options
  • Azure Service Level Agreements (SLAs)
  • Service Lifecycle in Azure

Module 5: 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

Module 6:Azure Storage Service

  • Storage Service and Account
  • Creating a Storage Account
  • Standard and Premium Performance
  • Understanding Replication
  • Hot, Cold and Archive Access Tiers
  • Working with Containers and Blobs
  • Types of Blobs
  • Block Blobs
  • Append Blobs
  • Page Blobs
  • Blob Metadata
  • Soft Delete
  • Azure Storage Explorer
  • Access blobs securely
  • Access Key
  • Account Shared Access Token
  • Service Shared Access Token
  • Shared Access Policy
  • Storage Service Encryption
  • Azure Key Vault

Module 7: 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

Module 8: 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

Module 9: Working with Copy Activity

  • Understanding Data Factory UI
  • Copy Data from Blob Storage to SQL Database
  • Copy data from storage account to storage account
  • Create Linked service o Create Dataset
  • Create Pipeline ∙ Integration Service
  • Copy Data from on-premise SQL Server to Blob Storage Working with Activities
  • Understanding Lookup Activity
  • Understanding for Each Activity
  • Filter Activity
  • Get Metadata Activity Azure
  • Lift and Shift
  • Provisioning Azure - SSIS Integration Runtime
  • Execute SSIS Packages from Azure
  • Execute SSIS Packages from SSISDB Triggers,
  • Monitoring Pipeline
  • Debug Pipeline
  • Trigger pipeline manually
  • Monitor pipeline
  • Trigger pipeline on schedule

Module 10 : 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

Module 11: Spark Basics

  • Spark Architecture
  • Spark RDD
  • Spark SQL
  • Spark SQL Functions
  • Spark SQL Advanced

Module 12:Python Basics

  • Python Basics
  • Python Data Types
  • Python Functions
  • Python Modules and packages
  • Python File handling
  • Python Data Structur

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