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Azure Data Factory Course Training
Microsoft Azure Data Factory Certification training offers the knowledge needed to use the data integration service. The course covers creating and managing data-driven workflows, moving and transforming data, data exploration, using Machine Learning capabilities, and managing and maintaining Azure Data Factory. Attendees gain comprehensive understanding of Azure data solutions and the concepts of data storage and data processing. Mastering these topics will enable students to implement the data integration solutions using Azure Data Factory and other Azure cloud computing services.
Why Chose Flair Technologies for Azure Data Factory Training?
AZURE DATA FACTORY
About Azure Data Factory:
Microsoft Azure Data Factory certification is a recognition for expertise in the use of Azure Data Factory, a cloud-based data integration service. This certification showcases one’s ability to design, implement, and monitor data pipelines and data-driven workflows. Azure Data Factory certification is highly valued in industries that handle massive amounts of data, requiring skills in data migration, transformation, and visualization. It certifies understanding of how to move and transform data, publish output data to data stores, or automate the extraction, transformation, and loading of data. This certification validates skills for roles such as data engineers and data architects, vital for optimizing business intelligence and data management strategies.
Azure Data Factory Course Outline:
Introduction
- Big Data Introduction
- Azure Data Factory Introduction
- Important Concepts in Azure Data Factory
- Create Azure Free Account for Azure Data Factory
Integration Runtime and Types
- Integration runtime in Azure Data Factory (Azure IR)
Azure Data Factory – Real-Time Use Cases
- Lab1: Create Your First Azure Data Factory
- Lab2: Create Your First Pipeline in Azure Data Factory
Azure Storage Account Integration with Azure Data Factory
- Lab3: Copy multiple files from blob to blob
- Lab4: Filter activity & Dynamic Copy Activity
- Lab5: Get File Names from Folder Dynamically
Deep Dive into Copy Activity in Azure Data Factory
- Lab6: Copy Activity Behavior in Azure Data Factory
- Lab7: Copy Activity Performance Tuning in Azure Data Factory
Validation in Azure Data Factory
- Lab8: Get Count of Files from Folder in Azure Data Factory
- Lab9: Validate Copied Data between Source and Sink in Azure Data Factory
Azure SQL Database Integration with Azure Data Factory
- Azure SQL Databases Introduction
- Relational Databases in Azure
- Creating Your First Azure SQL Database
- Deployment Models & Purchasing Modes
- Lab10: Overwrite and Append Modes in Copy Activity in Azure Data Factory
Full Load to Azure Synapse in Azure Data Factory
- Lab11: Copy Data from Azure SQL Database to Azure Synapse in Azure Data Factory
- Lab12: Copy Multiple Tables to Azure Synapse in Bulk with Lookup & ForEach in Data Factory
Logging and Notification with Azure Logic Apps
- Lab13: Log Pipeline Executions to SQL Table using Azure Data Factory
- Lab14: Custom Email Notifications & Send Error Notifications with Logic App
- Lab15: Use Foreach Loop Activity to Copy Multiple Tables – Step by Step Explanation
Incremental Load to Azure Synapse in Azure Data Factory
- Lab16: Incremental Load or Delta Load from SQL to Blob Storage in Azure Data Factory
- Lab17: Multi-Table Incremental Load or Delta Load from SQL to Azure Synapse
- Lab18: Incrementally Copy New and Changed Files Based on Last Modified Date
Azure Key Vault Integration with Azure Data Factory
- Lab19: Azure Key Vault – Secure Secrets, Keys & Certificates in Azure Data Factory
Azure Data Factory Triggers
- Event-Based Trigger in Azure Data Factory
- Lab21: Tumbling Window Trigger Dependency & Parameters
- Lab22: Schedule Trigger in Azure Data Factory
Self-Hosted Integration Runtime
- Lab23: Copying On-Premise Data using Azure Self-Hosted Integration Runtime
Data Migration from On-Premise SQL Server to Azure Synapse using Azure Data Factory
- Lab24: Load Data from On-Premise SQL Server to Azure Synapse
Data Migration to Azure Synapse with Polybase and Bulk Insert
- Lab25: Copy Data from SQL Server to Azure Synapse with Polybase & Bulk Insert
Data Migration from On-Premise File System to Azure Synapse using Azure Data Factory
- Lab26: Copy Data from On-Premise File System to Azure Synapse
Copying Data from REST API using Azure Data Factory
- Lab27: Loop through REST API to Copy Data to ADLS Gen2 Linked Service Parameters
Salesforce Integration with Azure Data Factory
- Lab28: Copy Data from Salesforce to ADLS Gen2 using ForEach & Copy in ADF V2
AWS S3 Integration with Azure Data Factory
- Lab29: Migrate Data from AWS S3 Buckets to ADLS Gen2 using ADF (v2)
Activities in Azure Data Factory
- Lab30: Switch Activity in Azure Data Factory & Copy, Move, and Delete Data
- Lab31: Until Activity in Azure Data Factory – Parameters & Variables
- Lab32: Copy Recent Files from Blob Input to Blob Output Folder without LPV
Snowflake Integration with Azure Data Factory
- Lab33: Copy Data from Azure Snowflake to Azure Synapse
Azure CosmosDB Integration with Azure Data Factory
- Lab34: Copy Data from Azure SQL DB to CosmosDB & Copy Data from Blob to CosmosDB
Advanced Concepts in Azure Data Factory
- Lab35: Nested ForEach in ADF & Pass Parameters from Master to Child Pipeline
- Lab36: 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
- Lab37: Aggregations and Derive Column Transformations
- Lab38: Joins in Azure Data Flows
- Lab39: Advanced Join Transformations with Filter and Conditional Split
Data Flows – Data Processing Use Case 1
- Lab40: Restart Data Processing from Failure
- Lab41: Remove Duplicate Rows & Store Summary Credit Stats in Azure Data Flows
- Lab42: Difference Between Join vs. Lookup Transformation & Merge Functionality
Dimensions in Data Flows
- Lab43: Slowly Changing Dimension Type 1 (SCD1) with HashKey Function and Load to Azure Synapse
- Lab44: Slowly Changing Dimension Type (SCD1) with SurrogateKey Transformation and Load to Azure Synapse
- Lab45: Slowly Changing Dimension Type 2 (SCD2) and Load to Azure Synapse
Data Flows – Data Processing Use Case 2
- Lab46: Flatten Transformation and Rank, Dense_Rank Transformations
- Lab47: Data Flows Performance Metrics and Data Flow Parameters
- Lab48: How to Use Pivot and Unpivot Transformations
- Lab49: Data Quality Checks and Logging using Data Flows
Batch Account Integration with Azure Data Factory
- Lab50: Custom Activity in Azure Data Factory
Azure Functions Integration with Azure Data Factory
- Lab51: Azure Functions Integration with Azure Data Factory
Azure HDInsight Integration with Azure Data Factory
- Lab52: Azure HDInsight with Spark Cluster
Azure Databricks Integration with Azure Data Factory
- Lab53: Azure Data Factory Integration with Azure Databricks
Azure Data Lake Analytics with Azure Data Factory
- Lab54: Azure Data Lake Analytics Integration with Azure Data Factory
Azure Machine Learning
- Lab55: Azure Machine Learning
Azure Automation Integration with Azure Data Factory
- Auto Termination of Server with Automation Account
Azure DevOps – CI/CD
- Lab56: Azure Data Factory CI/CD Pipeline
Azure Data Factory Projects
- Lab57: Azure Data Factory Project-1
- Lab58: Azure Data Factory Project-2
Azure Data Factory Interview Questions and Answers
- BI Master Program Interview Questions and Answers
Synapse Analytics
- Lab59: External Tables Creation in Azure Synapse
- Lab60: Project on Azure Synapse Workspace
Additional Content
- Python Basics
- Python Data Types
- Python Functions
- Python Modules and Packages
- Spark Architecture
- Spark RDD
- Spark SQL
- Spark SQL Functions
- Spark SQL Advanced
Remember that this is a detailed outline and can be adjusted based on the duration of the course, the depth of coverage desired for each topic, and the level of expertise of the participants. Additionally, as technology evolves, new tools and practices might emerge, so it’s essential to keep the course content up-to-date to reflect the latest trends and best practices.
Can You Get Job with ADF Certification?
Learning Microsoft Azure Data Factory course enhances skills in data integration and transformations, real-time analytics, and data-driven decision making. It opens doors to high-paying data engineering jobs. Statistically, Azure is used by over 85% fortune 500 companies, indicating a high demand for proficiency in this platform. Top companies like Microsoft, Amazon, Accenture, IBM, Capgemini, and Deloitte are constantly seeking Microsoft Azure Data Factory certified professionals. These industries require individuals who can manage and develop critical data processing systems. Their tasks involve data management, data integration, and the construction of robust data-driven frameworks.
What you will Learn in ADF Course?
The learning objectives of a Microsoft Azure Data Factory course include understanding the concept and significance of data factories and being able to implement and maintain them. Students will learn how to create data-driven workflows for orchestrating and automating data movement and data transformation across multiple data platforms. They will also master how to leverage Azure Data Factory to schedule big data jobs, manage and monitor data pipelines, and implement complex ETL processes. Additionally, this course intends to equip learners with proficiency in connecting to on-premises data sources and configuring data gateways, improving their overall familiarity with the Azure environment.
Who can Take this Course ?
Choose The Best
College Students those are interested to pursue their career as a ADF Engineer can take this program. This Program will help you get hired with attractive salary package after completing your college. This is the right time for you to utilize & learn as many skills that will help you in hiring as well as to get attractive salary.
This program will help you switch from your current domain to a Azure Data Factory. We had seen a huge number of working professional took this program & got amazing hikes, switched from boring jobs to a Azure Data Factory & even got 100% hike from their current salary.