Dive into the World of Azure with Our Azure Course
Are you ready to unlock the power of Azure and take your career to new heights? Look no further than our ‘Migrate SQL Workloads To Azure’ course, the gateway to mastering the dynamic world of Microsoft Azure. In this two-days instructor-led course, we bring you the expertise to comprehend Azure SQL Database and equip you with the knowledge required for seamless migration of MySQL and PostgreSQL workloads to Azure SQL Database.
Who Should Enroll?
This course caters to database developers planning to migrate their MySQL or Postgres DB workloads to Azure SQL DB, making it an invaluable asset for those seeking to propel their careers in database management. Even MySQL/Postgres administrators can benefit from the course by gaining a deep understanding of Azure SQL DB’s features and advantages.
What You'll Learn
With interactive lectures, PowerPoint presentations, discussions, and practical exercises, our methodology ensures a comprehensive grasp of the subject matter. By the end of the course, you’ll be proficient in migrating on-premises MySQL to Azure SQL DB for MySQL and on-premises PostgreSQL to Azure SQL DB for PostgreSQL, making you a sought-after professional in the world of cloud database management.
Don’t miss this opportunity to upskill and boost your career in the ever-evolving tech landscape. Join our Azure course today and be at the forefront of the Azure revolution!
Course Details
Course Code: -; Duration: 2 Days; Instructor Led
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Audience
Prerequisites
Methodology
This program will be conducted with interactive lectures, PowerPoint presentation, discussions, and practical exercise.
Course Objectives
Outlines
Module 1: Creating an ETL Solution
At the end of this module you will be able to implement data flow in a SSIS package.
Lessons
- Introduction to ETL with SSIS
- Exploring Source Data
- Implementing Data Flow
Lab: Implementing Data Flow in an SSIS Package
- Exploring source data
- Transferring data by using a data row task
- Using transformation components in a data row
After completing this module, you will be able to:
- Describe ETL with SSIS
- Explore Source Data
- Implement a Data Flow
Module 2: Implementing Control Flow in an SSIS Package
This module describes implementing control flow in an SSIS package.
Lessons
- Introduction to Control Flow
- Creating Dynamic Packages
- Using Containers
- Managing consistency.
Lab: Implementing Control Flow in an SSIS Package
- Using tasks and precedence in a control flow
- Using variables and parameters
- Using containers
Lab: Using Transactions and Checkpoints
- Using transactions
- Using checkpoints
After completing this module, you will be able to:
- Describe control flow
- Create dynamic packages
- Use containers
Module 3: Debugging and Troubleshooting SSIS Packages
This module describes how to debug and troubleshoot SSIS packages.
Lessons
- Debugging an SSIS Package
- Logging SSIS Package Events
- Handling Errors in an SSIS Package
Lab: Debugging and Troubleshooting an SSIS Package
- Debugging an SSIS package
- Logging SSIS package execution
- Implementing an event handler
- Handling errors in data flow
After completing this module, you will be able to:
- Debug an SSIS package
- Log SSIS package events
- Handle errors in an SSIS package
Module 4: Implementing a Data Extraction Solution
This module describes how to implement an SSIS solution that supports incremental DW loads and changing data.
Lessons
- Introduction to Incremental ETL
- Extracting Modified Data
- Loading modified data
- Temporal Tables
Lab: Extracting Modified Data
- Using a datetime column to incrementally extract data
- Using change data capture
- Using the CDC control task
- Using change tracking
Lab: Loading a data warehouse
- Loading data from CDC output tables
- Using a lookup transformation to insert or update dimension data
- Implementing a slowly changing dimension
- Using the merge statement
After completing this module, you will be able to:
- Describe incremental ETL
- Extract modified data
- Load modified data.
- Describe temporal tables
Module 5: Enforcing Data Quality
This module describes how to implement data cleansing by using Microsoft Data Quality services.
Lessons
- Introduction to Data Quality
- Using Data Quality Services to Cleanse Data
- Using Data Quality Services to Match Data
Lab: Cleansing Data
- Creating a DQS knowledge base
- Using a DQS project to cleanse data
- Using DQS in an SSIS package
Lab: De-duplicating Data
- Creating a matching policy
- Using a DS project to match data
After completing this module, you will be able to:
- Describe data quality services
- Cleanse data    using   data    quality services
- Match data using data quality services
- De-duplicate data using data quality services
Module 6: Deploying and Configuring SSIS Packages
This module describes how to deploy and configure SSIS packages.
Lessons
- Overview of SSIS Deployment
- Deploying SSIS Projects
- Planning SSIS Package Execution
Lab: Deploying and Configuring SSIS Packages
- Creating an SSIS catalog
- Deploying an SSIS project
- Creating environments for an SSIS solution
- Running an SSIS package in SQL server management studio
- Scheduling SSIS packages with SQL server agent
After completing this module, you will be able to:
- Describe an SSIS deployment
- Deploy an SSIS package
- Plan SSIS package execution
