Proximsoft’s Data Engineering Course: From Cloud Concepts to Practical Solutions

Categories Cloud, Data Engineering

We are thrilled to announce Proximsoft’s data engineering course. Crafted by industry professionals, this program empowers you with vital skills and knowledge essential for success in the dynamic field of data management and processing. At Proximsoft, we emphasize a hands-on approach, ensuring a blend of theoretical understanding and practical proficiency. Dive into comprehensive modules covering Cloud Computing Concepts, Azure Services, Security, Privacy, Compliance, Azure SQL Database, Azure Storage Service, Azure Data Lake, Azure Data Factory, and practical scenarios in Data Engineering. Acquire proficiency in essential tools, such as Azure Storage Explorer and Azure Key Vault. Engage in hands-on exercises to strengthen your expertise in crafting and optimizing data pipelines, working with Azure SQL, and mastering various data integration techniques. Join us to explore the world of data engineering technologies and methodologies.

Why Learn Data Engineering?

  • Data Engineering is a critical component in the era of big data, making it a highly sought-after skill in the job market.
  • Mastering Data Engineering allows you to design and implement scalable data solutions, contributing to organizational success.
  • Understanding cloud computing concepts and services, such as those provided by Azure, AWS, and Google Cloud, is crucial for modern data engineers.
  • Learn the intricacies of data storage, processing, and integration to build robust and efficient data pipelines.
  • Our course offers a hands-on approach, ensuring that you are well-prepared to apply your skills in real-world scenarios.
Mode of TrainingOnline live Interactive sessions
Duration of the Training6 weeks
Training duration per day 60 – 90 min session
Software AccessSoftware will be installed/server access will be provided, whichever is possible
Training MaterialsSoft copy of the material will be provided during the training 
Training feeDepends on the Requirement
Resume Preparation Yes, at the end of the course based on the JD
Interview PreparationYes, by sharing some FAQ’s
Mock callsYes, 2 Technical Mock calls 
Internship Project Yes
CertificationYes, at the end of the training
JOB Assistance Yes
JOB SupportYes
  
Weekdays6AM -2 PM EST & 6-11:30 PM EST (student can pick any  1 hr)
Weekends8 AM – 12 PM EST (student can pick any 2 hrs)

What I will learn?

  • Cloud Computing Concepts and Models
  • Azure Services for Data Engineering
  • Security, Privacy, and Compliance in Data Engineering
  • Azure SQL Database Management
  • Azure Storage Service and Data Lake
  • Azure Data Factory and Copy Activity
  • Practical Scenarios and Use Cases in Data Engineering

Course Content

Module 1: Cloud Computing Concepts
  • What is the “Cloud”?
  • Why cloud services
  • Types of cloud models
      • Deployment Models
  • Types of cloud services
  • Infrastructure as a Service
  • Platform as a Service
  • Software as a Service
  • Comparing Cloud Platforms
      • Microsoft Azure
  • 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
  • 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
  •  
Course level:All Levels
Course Duration: 30h

Requirements

  • Basic understanding of cloud computing.
  • Familiarity with relational databases.
  • General knowledge of SQL.
  • Ability to navigate and use basic command-line interfaces.

Talk to Our Career Advisor

    FAQ'S

    Data Engineering plays a crucial role in managing and processing large volumes of data, making it essential for organizations seeking actionable insights and efficient data utilization.
    A basic understanding of cloud computing concepts is beneficial, but our course caters to beginners, ensuring a smooth learning curve for all participants.
    Absolutely! The course emphasizes hands-on exercises, providing practical experience with Azure services to reinforce your learning.
    You'll need a basic understanding of cloud computing and familiarity with relational databases.

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