Implementing A SQL Data Warehouse
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About This Course
Course Description
This course provides students with the knowledge and skills to provision a Microsoft SQL Server database. The course covers SQL Server provision both on-premise and in Azure, and covers installing from a new and migrating from an existing install.
Learning Objectives
Describe the key elements of a data warehouse solution
Considerations for building a data warehouse
Implementing a logical design for a data warehouse
Implement a physical design for a data warehouse
Create Columnstore indexes
Implementing an Azure SQL Data Warehouse
Describe the key features of SSIS
Implement a data flow by using SSIS
Implement control flow by using tasks and precedence constraints
Create dynamic packages that include variables and parameters
Debug SSIS packages
Describe the considerations of implement an ETL Solution
Implement Data Quality Services
Implement a Master Data Service model
Describe how you can use custom components to extend SSIS
Deploy SSI projects
Describe BI and common BI scenarios
Inclusions
- Certified Instructor-led training
- Official Training Seminar Student Handbook
- Collaboration with classmates (not currently available for self-paced course)
- Real-world learning activities and scenarios
- Exam scheduling support*
- Enjoy job placement assistance for the first 12 months after course completion.
- This course is eligible for CCS Learning Academy’s Learn and Earn Program: get a tuition fee refund of up to 50% if you are placed in a job through CCS Global Tech’s Placement Division*
- Government and Private pricing available.*
Pre-requisites
- Basic knowledge of the Microsoft Windows operating system and its core functionality.
- Working knowledge of relational databases.
- Some experience with database design.
Target Audience
- Database professionals who need to fulfill a BI developer role focused on hands-on work by creating BI solutions, including data warehouse implementation, ETL and data cleansing
- Database professionals responsible for implementing a data warehouse, developing SSIS packages for data ETL, enforcing data integrity using Microsoft Data Services and cleansing data using Data Quality Services