Updating Your Skills to SQL Server 2017 - 10998 Course Outline
This two-day instructor led training course is aimed at database professionals looking to update their skills to cover SQL Server 2017.
The primary audience for this course is existing database professionals with experience of SQL Server 2016 who want to update their skills to SQL Server 2017.
The secondary audience is existing SQL Server 2016 MCSAs who want to prepare for the Upgrade exam for SQL Server 2017 certification.
In addition to their professional experience, students who attend this training should already have the following technical knowledge:
Experience of building and managing database, data warehouse, and business intelligence (BI) solutions with SQL Server 2016.
Familiarity with the Windows Server 2016 operating system and networking.
Familiarity with Microsoft Office 2016.
At course completion
After completing this course, students will be able to:
• Describe key capabilities and components of SQL Server 2017
• Describe new and enhanced features in SQL Server Performance, Availability, and Scalability
• Describe new and enhanced features in SQL Server data access
• Describe new and enhanced features in SQL Server reporting and BI
• Describe new and enhanced features in SQL Server OLAP
• Describe new and enhanced data analytics features
• Describe new and enhanced features in SQL Server Cloud deployments
• Describe SQL Server on Linux functionality
Module 1: Introduction to SQL Server 2017
Module Goal: Describe key capabilities and components of SQL Server 2017
Overview of SQL Server 2017
Functionality across versions
Module 2: What’s new in SQL Server Performance, Scalability, and Availability.
This module introduces the performance enhancements provided by Adaptive Query Processing and Automatic Tuning, as well as the scalability and availability enhancements provided by new Availability Group architectures, including Read-Scale Availability Groups and Availability Groups with SQL Server on Linux
Adaptive query processing
Lab : Performance and availability – adaptive query processing
Batch mode memory grant feedback
Batch mode adaptive joins
Module 3: What’s New in SQL Server data Access
SQL Server 2017 introduces SQL Graph which enables you to define the relationships between your data items in a table rather than calculating them during a query, reducing the query cost and simplifying your data structure.
Lab : SQL Graph
Create a Graph database
Query a Graph database
Module 4: What’s new in SQL Server Reporting and BI
This module describes what’s new in SQL Server reporting and BI.
Power BI report Server
Reporting Services update
Lab : Reporting and BI
Deploy Power BI report server
Add commenting to a report
Module 5: New and Enhanced Features in SQL Server Analysis Services
This module introduces new and enhanced features in SQL Server Analysis Services, with particular emphasis on the tabular data model.
Tabular model updates
Lab : Ragged hierarchies
View existing reports
Hide blank members
Module 6: New and Enhanced data Analytics Features
This module introduces new and enhanced data analytics features.
New and enhanced data analytics features
Lab : Data analytics with Python
Enable external script execution
Run Python scripts
Module 7: What’s new in SQL Server in the Cloud
Organizations want the best value from a mixture of cloud services and their existing investment in on-premises hardware and software. This module covers a comparison between the features of Microsoft Azure SQL Database and Microsoft SQL Server 2017, as well as new features that make it easier for you to migrate databases from on-premises SQL Server instances to Azure SQL Database.
Azure SQL database features
Lab : Managed instances
Module 8: SQL Server on Linux
This module covers the features of SQL Server on Linux, as well as the process for deploying SQL Server on Linux and using Docker.
SQL Server on Linux
Deploying SQL Server on Linux
Lab : SQL Server in Docker containers
Deploy a SQL Server Docker image
Run a SQL Server instance inside a Docker container
Connect to a SQL Server Instance running in a Docker container
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