SQL Server 2017 is the first SQL Server version that can be installed on Windows, Linux and inside a Docker container. This stairway series serves as a guide for the experienced SQL Server DBA to acquire skills and knowledge on this platform. This is an introductory series to installing Linux and SQL Server on Linux.
SSAS (SQL Server Analysis Services) is available in two modes, tabular and multidimensional. The new tabular model is easier for those companies who are not already invested in the traditional, multidimensional model. In this stairway, Thomas LeBlanc will teach you how to create tabular models used for reports and dashboards.
Azure SQL Database is Microsoft’s fully managed cloud relational database service in Microsoft Azure. With many companies moving to cloud based solutions Azure SQL Database is a leading option for the data tier that many consider.
The aim of this stairway course is to give you a comprehensive practical guide on how to begin creating Azure SQL Databases whilst trying to convey some very important practical knowledge on the way. This stairway course assumes that you have absolutely no knowledge of Azure and after completing it you will become comfortable with creating logical SQL servers, databases, correct security configuration around firewalls and logins hence allowing you to connect to the database via SQL Server Management Studio.
This is a series designed to help you learn more about Machine Learning Services using both R and Python. We will cover the architecture, installation, configuration, and use of Machine Learning Services to run complex analysis on your data.
In addition to the data that our clients and customers store in a database, there is a tremendous amount of meta data, ‘data about data’, that describes how the database is set up, configured, and what the properties are for the various objects. This stairway aims to demystify and explain how you can query and use this meta data to more effectively manage your SQL Server Databases.
As Microsoft continues to expand the Azure platform, they have enhanced its ability in ways that are quite different from what we’ve come to expect from SQL Server. Learn about the new language from Microsoft, U-SQL, designed to work with Data Lakes and Big Data in Azure.
This stairway will examine Dynamic Data Data Masking, introduced in Azure SQL Database and SQL Server 2016. This should allow you to implement Dynamic Data Masking in your application, understanding the implications of the various masks used on different datatypes.
Erin Stellato, a Principal Consultant with SQLskills.com, explores the use of Extended Events as a diagnostic data collection tool or SQL Server. She describes how to define efficient low-overhead event sessions that exploit fully the vast number of events, as well as the powerful filtering and data collection options, offered by this new event collection infrastructure. She also demonstrates simple techniques to analyze event data and identify and troubleshoot the causes of poor SQL Server performance, such as long-running queries that consume vast amounts of CPU and I/O resources. It is time to embrace Extended Events and understand all that it has to offer, and Erin’s stairway is the perfect place to start.