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Intermediate Level
Azure Data Factory (ADF)
★ 4.8
(300 learners)
60 hrs total 3 modules
Microsoft Azure Azure DevOps Databricks Azure Data Factory LangChain
Only 8 seats left
· Next batch starts 22 Aug 2026
- 60 hrs
- of content
- 3 modules
- in curriculum
- 16 projects
- hands-on builds
- Intermediate
- difficulty
Curriculum covers
Frameworks you'll master
Microsoft Azure Azure DevOps Databricks Azure Data Factory LangChain
Course Curriculum
3 modules · 60 hours · 24 live sessions
AZURE DATA FACTORY (ADF) 21 sessions
- ADF Overview
- Azure Data Factory (ADF) Overview
- Azure Storage Solutions Overview
- Environment Setup
- Creating Azure Data Factory
- Creating Azure Storage Account
- Creating Azure Data Lake Storage Gen2
- Creating Azure SQL Database
- Installing Azure Studio
- Data Ingestion from Azure BLOB
- Data Ingestion from Azure BLOB Module Overview
- Copy Activity Overview
- Naming Standards
- Linked Services & Data Sets
- Control Flow Activities Validation Activity
- Control Flow Activities Get Metadata, If Condition, Web Activities
- Control Flow Activities Delete Activity
- ADF Triggers Overview
- Creating Event Trigger
- Data Ingestion From HTTP
- Data Ingestion from HTTP Module Overview
- ECDC Data Overview
- Create Pipeline
- Pipelines Variables
- Pipeline Parameters & Schedule Trigger
- Control Flow Activities
- Linked Service Parameters
- Metadata Driven Pipeline
- Data Flows Cases & Deaths Data Transformation
- Data Flows Module Overview
- Introduction to Data Flows
- Data Flow UI Overview
- Transformation Requirement Overview
- Source Transformation
- Filter Transformation
- Select Transformation
- Pivot Transformation
- Lookup Transformation
- Sink Transformation
- Create ADF Pipelines
- Data Flows Hospital Admissions Data Transformation
- Data Flows Module Overview
- Transformation Requirement
- Source Transformation (Assignment)
- Select Transformation (Assignment)
- Lookup Country (Assignment)
- Conditional Split Transformation
- Source Transformation Dim Date
- Derived Column Transformation
- Aggregate Transformation
- Join Transformation
- Pivot Transformation (Assignment)
- Sort Transformation
- Sink Transformation (Assignment)
- Create ADF Pipeline (Assignment)
- Prepare Data for HDInsight & Databricks
- HDInsight Activity
- HDInsight Activity Module Overview
- Create HDInsight Cluster
- Tour of HDInsight UI
- Transformation Requirement
- Hive Script Walkthrough
- Create ADF Pipeline with Hive Acitivity
- Delete HDInsight Cluster
- Databricks Activity
- Data Bricks Activity Module Overview
- Create Azure Databricks Service
- Create Azure Databricks Cluster
- Mounting Azure Data Lake Storage
- Transformation Requirements
- Create ADF Pipeline Databricks Notebook Activity
- Copy Data to Azure SQL
- Copy Data to Azure SQL Module Overview
- Copy Data Activity Cases & Deaths Data
- Copy Data Activity Hospital Admissions
- Copy Data Activity Testing Data
- Making Pipelines Production Ready
- Making Pipelines Production Ready Module Overview
- Option 1 Pipeline Dependency
- Option 2 Trigger Dependency
- Monitoring
- Monitoring Module Overview
- Azure Data Factory Monitor
- Creating Alerts
- Monitor Pipeline Failures
- Rerun Failed Pipelines
- Reporting on Metrics
- Introduction to Azure Monitor
- Azure Data Factory Analytics
- Metadata Driven Ingestion Pipeline
- Creation of Metadata tables to capture pipeline failure
- Trigger alerts/notifications on Pipeline Failure
- Continuous Integration/Continuous Delivery (CI/CD)
- Continuous Integration/Continuous Delivery (CI/CD) Module Overview
- Introduction to Continuous Integration/Continuous Delivery (CI/CD)
- Introduction to CI/CD for Azure Data Factory
- Overview of Azure DevOps
- Azure DevOps Environment Setup
- Azure Data Factory Environment Setup
- Azure Data Factory Git Configuration
- Azure Data Factory Code Development using Git
- Release Pipeline Design
- Creating ARM Deployment Tasks
- Pipeline Variables
- Add Production Stage
- YAML Build Pipeline Script Walkthrough
- Update Release Pipeline Building as AI LangChain Chat Assistant
m) CI/CD Scenario Data Lake Access 3 sessions
- Access to Data Lake Storage Overview
- Data Lake Storage Setup
- Using Managed Identity Grant access to Data Lake
- Using Managed Identity Create Data Factory Pipelines
- Using Managed Identity Release Pipelines changes
- Using Access Keys Solution Options Overview
- Using Access Keys Key Vault Setup
- Using Access Keys Create Data Factory Pipeline
- Using Access Keys Release Pipeline Changes Prompt Engineering
- Azure Service Pointers:
- 1) ADF (Azure Data Flows) is used for medium transformations, Also, it's a codefree Transformation Tool whereas HDInsight & Azure Databricks is used for Complex Transformations.
- 2) Azure Synapse Analytics formerly called Azure DW & it's based on massive parallel processing architecture. Here we are using Azure SQL Database but we are storing very less data.
- 3) Azure DataLake is built on top of Azure BLOB Storage with enhance performance, enhance management & Better security.
- 4) Azure Dataflow is a part of Data Factory.
Batch Orchestration: 1 sessions
- Data is Ingested from Source system into Azure Storage Account (BLOB storage)
- Data is Ingested from Source system into Azure Storage Account (BLOB storage)
Batch Schedule
⚡ Seats filling fast — only 8 remaining across all batches
| Batch Type | Schedule | Duration | Next Start Date | Availability |
|---|---|---|---|---|
| Weekend | Sat & Sun, 10am–1pm | 10 weeks | 22 Aug 2026 | Available |
| Weekday | Mon–Fri, 7–9pm | 8 weeks | 24 Aug 2026 | Available |
| Fast-track | Mon–Sun, 6 hours/day | 2 weeks | 31 Aug 2026 | Available |
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