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# Azure Data Integration Pipeline Training
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## A Day of Fundementals
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___
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## Overview
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___
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## Agenda
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The following offers an insight into the complete agenda and module breakdown for this workshop.
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___
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# Azure Data Integration Pipeline Training
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## Advanced Design & Delivery (A Deep Dive)
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___
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## Overview
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In this course we'll quickly cover the fundamentals of data integration pipelines before going much deeper into our Azure resources.
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Within a typical Azure data platform solution for any enterprise grade data analytics or data science workload an umbrella resource is needed to trigger, monitor, and handle the control flow for transforming datasets, with the goal being actionable data insight. Those requirements are met by deploying Azure Data Integration pipelines, delivered using Azure Synapse Analytics or Azure Data Factory. In this session, I'll show you how to create rich dynamic data pipelines and apply these orchestration resources in production. Using scaled architecture design patterns, best practice, data mesh principals, and the latest metadata driven frameworks. We will take a deep dive into the services, considering how to build custom activities, complex pipelines and think about hierarchical design patterns for enterprise grade deployments. All this and more in a complete set of 12 modules (based on real world experience) we will take you through how to implement data integration pipelines in production and delivered advanced orchestation patterns.
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If that's not enough learning for you, a set of hands-on labs will also be made available that you can work through at your own pace. Whether you are new to Azure Data Integration Pipelines or have some experience, you will leave this course with new skills, ideas, and a much deeper understanding of the resources for your future data platform projects.
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___
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## Agenda
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The following offers an insight into the complete agenda and module breakdown for this course.
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### Day 1
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* __Module 1:__ [Pipeline Fundamentals]()
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* The History of Azure Orchestration
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* Synapse Analytics vs Data Factory
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* Integration Components
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* Common Activities
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* Execution Dependencies
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___
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* __Module 2:__ [Integration Runtime Design Patterns]()
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* Compute Types
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* Azure
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* Hosted
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* SSIS
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* Patterns & Configuration
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___
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* __Module 3:__ [Data Transformation]()
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* Data Flows
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* Power Query Injection
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* Spark Configuration
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* Use Cases
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___
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* __Module 4:__ [Dynamic Pipelines]()
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* Expressions & Interpolation
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* Simple Metadata Driven Execution
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* Dynamic Content Chains
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* Reference Names
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___
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* __Module 5:__ [Pipeline Extensibility]()
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* Azure Batch Service
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* Tasks
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* Compute Pools
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* Scaling
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* Pipeline Custom Activities
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* Azure Management API
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* Azure Functions
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___
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* __Module 6:__ [Execution Parallelism]()
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* Control Flow Scale Out
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* Concurrency Limitations
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* Internal vs External Activities
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* Orchestration Framework - [procfwk.com](http://procfwk.com/)
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___
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### Day 2
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* __An Architects Recap__: [Modules 1 to 6]()
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* Design
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* Extract
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* Transform
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* Load
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___
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* __Module 7:__ [VNet Integration]()
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* Private Endpoints
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* Managed VNet's
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* Firewall Bypass
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___
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* __Module 8:__ [Security]()
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* Service Principals
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* Managed Identities
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* Azure Key Vault Integration
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* Customer Managed Keys
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* Pipeline Access & Permissions
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___
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* __Module 9:__ [Monitoring & Alerting]()
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* Studio Monitoring
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* Log Analytics & Kusto Queries
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* Operational Dashboards
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* Advanced Alerting
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* __Module 10:__ [Solution Testing]()
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* Development Time Validation
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* Test Coverage
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* NUnit Tests
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___
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* __Module 11:__ [CI/CD]()
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* Source Control vs Developer UI
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* Basic ARM Template Deployments
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* Advanced Deployment Patterns
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___
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* __Module 12:__ [Final Thoughts]()
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* Running Costs
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* Conclusions
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* Best Practices
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___
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# Azure Data Integration Pipeline Training
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## Advanced Design & Delivery
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___
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## Overview
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||||
|
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In this course we'll quickly cover the fundamentals of data integration pipelines before going much deeper into our Azure resources.
|
||||
|
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Within a typical Azure data platform solution for any enterprise grade data analytics or data science workload an umbrella resource is needed to trigger, monitor, and handle the control flow for transforming datasets, with the goal being actionable data insight. Those requirements are met by deploying Azure Data Integration pipelines, delivered using Azure Synapse Analytics or Azure Data Factory. In this session, I'll show you how to create rich dynamic data pipelines and apply these orchestration resources in production. Using scaled architecture design patterns, best practice, data mesh principals, and the latest metadata driven frameworks. We will take a deep dive into the services, considering how to build custom activities, complex pipelines and think about hierarchical design patterns for enterprise grade deployments. All this and more in a complete set of 12 modules (based on real world experience) we will take you through how to implement data integration pipelines in production and delivered advanced orchestation patterns.
|
||||
|
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If that's not enough learning for you, a set of hands-on labs will also be made available that you can work through at your own pace. Whether you are new to Azure Data Integration Pipelines or have some experience, you will leave this course with new skills, ideas, and a much deeper understanding of the resources for your future data platform projects.
|
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|
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___
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||||
|
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## Agenda
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|
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The following offers an insight into the complete agenda and module breakdown for this course.
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|
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* __Module 1:__ [Pipeline Fundamentals]()
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||||
* The History of Azure Orchestration
|
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* Synapse Analytics vs Data Factory
|
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* Integration Components
|
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* Common Activities
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* Execution Dependencies
|
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|
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___
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* __Module 2:__ [Integration Runtime Design Patterns]()
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* Compute Types
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* Azure
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* Hosted
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* SSIS
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* Patterns & Configuration
|
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___
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* __Module 3:__ [Data Transformation]()
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* Data Flows
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* Power Query Injection
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* Spark Configuration
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* Use Cases
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___
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* __Module 4:__ [Dynamic Pipelines]()
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* Expressions & Interpolation
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* Simple Metadata Driven Execution
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* Dynamic Content Chains
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* Reference Names
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___
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* __Module 5:__ [Pipeline Extensibility]()
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* Azure Batch Service
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* Tasks
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* Compute Pools
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* Scaling
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* Pipeline Custom Activities
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* Azure Management API
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* Azure Functions
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___
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* __Module 6:__ [Execution Parallelism]()
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* Control Flow Scale Out
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* Concurrency Limitations
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* Internal vs External Activities
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* Orchestration Framework - [procfwk.com](http://procfwk.com/)
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___
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* __Module 7:__ [VNet Integration]()
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* Private Endpoints
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* Managed VNet's
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* Firewall Bypass
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___
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* __Module 8:__ [Security]()
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* Service Principals
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* Managed Identities
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* Azure Key Vault Integration
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* Customer Managed Keys
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* Pipeline Access & Permissions
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___
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* __Module 9:__ [Monitoring & Alerting]()
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* Studio Monitoring
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* Log Analytics & Kusto Queries
|
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* Operational Dashboards
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* Advanced Alerting
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* __Module 10:__ [Solution Testing]()
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* Development Time Validation
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* Test Coverage
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* NUnit Tests
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___
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* __Module 11:__ [CI/CD]()
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* Source Control vs Developer UI
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* Basic ARM Template Deployments
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* Advanced Deployment Patterns
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___
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* __Module 12:__ [Final Thoughts]()
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* Running Costs
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* Conclusions
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* Best Practices
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___
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# Azure Data Integration Pipeline Training
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## Fundamentals to Level 300
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___
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## Overview
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||||
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|
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___
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## Agenda
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|
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The following offers an insight into the complete agenda and module breakdown for this workshop.
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|
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___
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Before Width: | Height: | Size: 176 KiB |
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# Azure Data Integration Pipeline Training
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## Zero to Level 401
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___
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## Overview
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|
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___
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|
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## Agenda
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|
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The following offers an insight into the complete agenda and module breakdown for this course.
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|
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* __Module 1:__ [Pipeline Fundamentals]()
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* The History of Azure Orchestration
|
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* Synapse Analytics vs Data Factory
|
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* Integration Components
|
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* Common Activities
|
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* Execution Dependencies
|
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|
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___
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|
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* __Module 2:__ [Integration Runtime Design Patterns]()
|
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* Compute Types
|
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* Azure
|
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* Hosted
|
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* SSIS
|
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* Patterns & Configuration
|
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|
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___
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* __Module 3:__ [Data Transformation]()
|
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* Data Flows
|
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* Power Query Injection
|
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* Spark Configuration
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* Use Cases
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___
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|
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* __Module 4:__ [Dynamic Pipelines]()
|
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* Expressions & Interpolation
|
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* Simple Metadata Driven Execution
|
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* Dynamic Content Chains
|
||||
* Reference Names
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||||
|
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___
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* __Module 5:__ [Pipeline Extensibility]()
|
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* Azure Batch Service
|
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* Tasks
|
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* Compute Pools
|
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* Scaling
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* Pipeline Custom Activities
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* Azure Management API
|
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* Azure Functions
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___
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* __Module 6:__ [Execution Parallelism]()
|
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* Control Flow Scale Out
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* Concurrency Limitations
|
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* Internal vs External Activities
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* Orchestration Framework - [procfwk.com](http://procfwk.com/)
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||||
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___
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* __Module 7:__ [VNet Integration]()
|
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* Private Endpoints
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* Managed VNet's
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* Firewall Bypass
|
||||
|
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___
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* __Module 8:__ [Security]()
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* Service Principals
|
||||
* Managed Identities
|
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* Azure Key Vault Integration
|
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* Customer Managed Keys
|
||||
* Pipeline Access & Permissions
|
||||
|
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___
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* __Module 9:__ [Monitoring & Alerting]()
|
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* Studio Monitoring
|
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* Log Analytics & Kusto Queries
|
||||
* Operational Dashboards
|
||||
* Advanced Alerting
|
||||
|
||||
* __Module 10:__ [Solution Testing]()
|
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* Development Time Validation
|
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* Test Coverage
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* NUnit Tests
|
||||
|
||||
___
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||||
|
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* __Module 11:__ [CI/CD]()
|
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* Source Control vs Developer UI
|
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* Basic ARM Template Deployments
|
||||
* Advanced Deployment Patterns
|
||||
|
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___
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* __Module 12:__ [Final Thoughts]()
|
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* Running Costs
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* Conclusions
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* Best Practices
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___
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14
README.md
14
README.md
@ -5,20 +5,20 @@
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Hey friends and welcome to my training workshops on __Azure Data Integration Pipelines__.
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Over the coming hours or days (depending on your choosen workshop) we will be all becoming pipeline workers!... And I completely recommend this description when describing your job to non-technical family members. But be warned, if you go on to tell them that the factory of pipes is in the cloud for orchestration and integration you are likely to be branded as crazy. However, here and now that is ok. You are amongst like-minded geeky friends that all want to become cloud pipeline workers that doing data plumbing with data pipes as well :-)
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Over the coming hours or days (depending on your chosen workshop) we will be all becoming pipeline workers!... And I completely recommend this description when describing your job to non-technical family members. But be warned, if you go on to tell them that the factory of pipes is in the cloud for orchestration and integration you are likely to be branded as crazy. However, here and now that is ok. You are amongst like-minded geeky friends that all want to become cloud pipeline workers that doing data plumbing with data pipes as well :-)
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On a more serious note, throughout our day of training you will quickly notice, like with most technologies, there are an awful lot of different ways you can implement Azure orchestration services and understanding the best way to do something is often the biggest challenge. That said, if you only take away one thing from this training, I will ask that you have an appreciation of this fact; in depends! Then when delviering solutions you take a step back from the requirements and think about the overall technical design and how Azure Integration Pipelines should fit into your platform as a core component.
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On a more serious note, throughout our day of training you will quickly notice, like with most technologies, there are an awful lot of different ways you can implement Azure orchestration services and understanding the best way to do something is often the biggest challenge. That said, if you only take away one thing from this training, I will ask that you have an appreciation of this fact; in depends! Then when delivering solutions you take a step back from the requirements and think about the overall technical design and how Azure Integration Pipelines should fit into your platform as a core component.
|
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|
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All too often with new and shiny services we start playing around then try to make the technology fit our solution. Rather than thinking about the solution requirements and which technology meets our needs. This is true of all developers, I don't want to preach, so am simply asking that we take a growth mindset. Think about the outputs and the requirements as a goal.
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___
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## Workshops
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- A Day of Fundementals - 1 Day
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- Fundamentals to Level 300 - 1 Day
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- Advanced Design & Delivery - 1 Day
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- [Advanced Design & Delivery (A Deep Dive) - 2 Day](./Content/Advanced%20Design%20%26%20Delivery%20(A%20Deep%20Dive)%20-%202%20Day/Agenda.md)
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- Zero to Level 401 - 3 Day
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1. [A Day of Fundamentals - 1 Day](./Content/01.%20A%20Day%20of%20Fundamentals%20-%201%20Day/01.%20Agenda.md)
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2. [Fundamentals to Level 300 - 1 Day](./Content/02.%20Fundamentals%20to%20Level%20300%20-%201%20Day/02.%20Agenda.md)
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3. [Advanced Design & Delivery - 1 Day](./Content/03.%20Advanced%20Design%20%26%20Delivery%20-%201%20Day/03.%20Agenda.md)
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4. [Advanced Design & Delivery (A Deep Dive) - 2 Day](./Content/04.%20Advanced%20Design%20%26%20Delivery%20(A%20Deep%20Dive)%20-%202%20Day/04.%20Agenda.md)
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5. [Zero to Level 401 - 3 Day](./Content/05.%20Zero%20to%20Level%20401%20-%203%20Day/05.%20Agenda.md)
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___
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|
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## Speaker Biography
|
||||
|
||||
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