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Azure Data Factory
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Frequently Asked Questions
What is ADF and What are it's uses?
Azure Data Factory is Azure's cloud ETL service for scale-out serverless data integration and data transformation. It offers a code-free UI for intuitive authoring and single-pane-of-glass monitoring and management. You can also lift and shift existing SSIS packages to Azure and run them with full compatibility in ADF.
Is ADF easy to learn?
It is easy to learn because of simple cloud service, processes and many low code interfaces.
Does ADF have a market?
Yes, Microsoft is the leader in Analytics and Business Intelligence since 16 years. It is providing its wonderful support to the current cutting edge processes and technologies by its monthly updates. And also On-Premise MSBI and Cloud Power BI providing other BI supportive services beside Azure BI. Kindly visit the following links to know more about the Azure BI Market & Leadership - https://powerbi.microsoft.com/en-us/blog/microsoft-named-a-leader-in-the-2022-gartner-magic-quadrant-for-analytics-and-bi-platforms/ - https://powerbi.microsoft.com/en-my/blog/microsoft-named-a-leader-in-the-forrester-wave-augmented-bi-platforms-q3-2021/
What if I miss a training session?
No need to worry, daily videos are in the class room folder and materials in the materials folder. You can watch and practice and also reach out to the trainer for queries
What type of study materials and videos we will get and how long they are available?
You will get all materials after a week of your joining which you can download and use. Daily live class recordings will be placed in a folder and you will have access for maximum 12 months. Lab practice documents and required Power BI credentials provided for practice till one year.
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Curriculum
Cloud Computing Concepts
- What is the "Cloud"?
- Â Why cloud services
- Â Types of cloud models
- Â Deployment Models
- Â Private Cloud deployment model
- Â Public Cloud deployment model
- Â Hybrid cloud deployment model
- Â Characteristics of cloud computing
- Â On-demand self-service
- Â Multi-tenancy and resource pooling
- Â Measured service
- Â Cloud Data Warehouse Architecture
- Â Shared Memory architecture
- Â Shared Disk architecture
- Â Shared Nothing architecture
Core Azure services
- Core Azure Architectural components
- Â Core Azure Services and Products
- Â Azure solutions
- Â Azure management tools
- Â DWH Life Cycles
- Â DWH Approaches (INMON and KIMBALL)
- Â Data Granularity, Data movement stages
Azure Pricing and Support
- Azure subscriptions
- Â Planning and managing costs
- Azure support options
- Â Azure Service Level Agreements (SLAs)
- Â Service Lifecycle in Azure
Azure SQL Database
- Introduction Azure SQL Database
- Â Comparing Single Database
- Managed Instance
- Â Creating and Using SQL Server
- Â Azure SQL Database Tools
- Â Migrating on premise database to SQL Azure
- Â Purchasing Models
- Â DTU service tiers
- Â vCore based Model
- Â Server-less compute tier
- Â Service Tiers
- Â General purpose / Standard
- Â Business Critical / Premium
- Â Hyperscale
- Â Deployment of an Azure SQL Database
- Â What is SQL elastic pools
- Â Choosing the correct pool size
- Â Creating a New Pool
- Â Manage Pools
- Â Monitoring and Tuning Azure SQL Database
- Â Configure SQL Database Auditing
- Â Export and Import of Database
Azure Storage Service
- Storage Service and Account
- Â Creating a Storage Accounte
- Standard and Premium Performance
- Â Understanding Replication
- Â Hot, Cold and Archive Access Tiers
- Â Working with Containers and Blobs
- Â Types of Blobs
- Â Block Blobs,
- Append Blobs
- Â Page Blobs
- Â Blob Metadata
- Â Soft Delete
- Â Azure Storage Explorer
- Â Access blobs securely
- Â Access Key
- Â Account Shared Access Token
- Â Service Shared Access Token
- Â Shared Access Policy
- Â Storage Service Encryption
- Â Azure Key Vault
Azure Data Factory
- What is Data Factory?
- Â Data Factory Key Components
- Pipelinee
- Â Activity
- Â Linked Service
- Â Data Set
- Â Integration Runtime
- Â Triggers
- Data Flows
- Â Page Blobs
- Â Integration Runtime Provision Required Azure Resources
- Â Create Resource Group
- Â Create Storage Account
- Provision SQL Server and Create Database
- Provision Azure Data Factory (ADF) Service
Exploration of Copy Activity
- Understanding Data Factory UI
- Â Copy Data from Blob Storage to SQL Database
- Copy data from storage account to storage account
- Â Create Linked service and Create Dataset
- Â Create Pipeline - Integration Service
- Â Copy Data from on-premise SQL Server to Blob Storage Working with Activities
- Â Understanding Lookup Activity
- Â Understanding for Each Activity
- Filter Activity
- Â Get Metadata Activity Azure
- Â Lift and Shift
- Â Provisioning Azure - SSIS Integration Runtime
- Â Execute SSIS Packages from Azure
- Execute SSIS Packages from SSISDB Triggers,
- Monitoring Pipeline
- Debug Pipeline
- Trigger pipeline manually
- Monitor pipeline
- Trigger pipeline on schedule
Scenarios and Use Cases Explanation
- ADF Introduction
- Â Important Concepts in ADF
- Create Azure Free Account for ADF
- Â Integration Runtime and Types
- Â Integration runtime in ADF-Azure IR
- Â Create Your First ADF
- Â Create Your First Pipeline in ADF
- Â Azure Storage Account Integration with ADF
- Copy multiple files from blob to blob
- Â Filter activity __ Dynamic Copy Activity
- Â Get File Names from Folder Dynamically
- Â Deep dive into Copy Activity in ADF
- Â 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 ADFs
- 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 Data Flows
- 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 Transformatioss
- 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 ADFF
- Azure Databricks Integration with ADF
- ADF Integration with Azure Databricks
- Azure Data Lake Analytics integration with ADF
Introduction to Azure Databricks
- Introduction to Databricks
- Â Azure Databricks Architecture
- Azure Databricks Main Concepts
- Â Databricks Integration with Azure Blob Storage (Read data from Blob Storage and Create Blob mount point)
Introduction to Python
- Features of Python
- Â Python Virtual Machine (PVM)
- Frozen Binaries
- Â Memory management in Python
- Â Garbage collection in Python
Projects Covered
Project - 01
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Project - 02
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