Learn to implement a data warehouse platform with Microsoft SQL Server 2016.
In 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 new and migrating from an existing install.
Što ćete naučiti
- Describe the key elements of a data warehousing solution
- Describe the main hardware consideration for building a data warehouse
- Implement 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 control flow by using tasks and precedence constraints
- Create dynamic packages that include variables and parameters
- Debug SSIS packages
- Describe the considerations for implement an ETL solution
- Implement Data Quality Services
- Implement a Maser Data Services model
- Describe how you can use custom components to extend SSIS
- Deploy SSIS projects
- Describe BI and common BI scenarios
Kome je namijenjeno
- 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
Preduvjeti
- Basic knowledge of the Microsoft Windows operating system and its core functionality.
- Working knowledge of relational databases.
- Some experience with database design
Nastavni plan
Pregledaj
- 1. Introduction to Data Warehousing
- Overview of Data Warehousing
- Considerations for a Data Warehouse Solution
- Considerations for Building a Data Warehouse
- Planning data warehouse hardware
- Data warehouse design overview
- Designing dimension tables
- Designing fact tables
- Physical Design for a Data Warehouse
- Introduction to Columnstore Indexes
- Creating Columnstore Indexes
- Working with Columnstore Indexes
- Advantages of Azure SQL Data Warehouse
- Implementing an Azure SQL Data Warehouse
- Developing an Azure SQL Data Warehouse
- Migrating to an Azure SQ Data Warehouse
- Copying data with Azue data factory
- Introduction ETL with SSIS
- Exploring Source Data
- Implementing Data Flow
- Introduction to Control Flow
- Creating Dynamic Packages
- Using Containers
- Managing consistency
- Debugging an SSIS Package
- Logging SSIS Package Events
- Handling Errors in Data Flow
- Introduction to Incremental ETL
- Extracting Modified Data
- Loading Modified Data
- Temporal Tables
- Introduction to Data Quality
- Using Data Quality Services to Cleanse Data
- Using Data Quality Services to Match Data
- Introduction to Master Data Services Concepts
- Implementing a Master Data Services Model
- Hierarchies and Collections
- Creating a Master Data Hub
- Using Custom Components in SSIS
- Using Scripting in SSIS
- Overview of SSIS Deployment
- Deploying SSIS Projects
- Planning SSIS Package Execution
- Introduction to Business Intelligence
- An Introduction to Data Analysis
- Introduction to Reporting
- Analyzing Data with Azure SQL Data Warehouse
- Lab 1: Exploring a Data Warehouse Solution
- Lab 2: Planning Data Warehouse Infrastructure
- Lab 3: Implementing a Data Warehouse Schema
- Lab 4: Using Columnstore Indexes
- Lab 5: Implementing an Azure SQL Data Warehouse
- Lab 6: Implementing Data Flow in an SSIS Package
- Lab 7: Implementing Control Flow in an SSIS Package
- Lab 8: Using Transactions and Checkpoints
- Lab 9: Debugging and Troubleshooting an SSIS Package
- Lab 10: Extracting Modified Data
- Lab 11: Loading a data warehouse
- Lab 12: Cleansing Data
- Lab 13: De-duplicating Data
- Lab 14: Implementing Master Data Services
- Lab 15: Using Scripts
- Lab 16: Deploying and Configuring SSIS Packages
- Lab 17: Using a Data Warehouse