Learn to leverage predictive models and methods directly in SQL Server. This course will demonstrate the capabilities of SQL Server related to predictive analytics, including best practices and optimizations.
SQL Server remains one of the most popular data platforms on the planet. Many industries want to leverage popular predictive models using SQL Server and recent features, enhancements, and the power of the cloud have made this more accessible than ever. In this course, Predictive Analysis with SQL Server, you'll learn how to prepare data for predictive analytics within SQL Server. First, you'll see some of the most popular methods for predictive models, such as regressions and clustering, demonstrated with hands-on demos and code samples. Next, you'll dig into analyzing the effectiveness of these queries. Finally, you'll explore optimizing the SQL Server platform for these types of analytical workloads. By the end of this course, you'll have the skills and knowledge of building a predictive model directly in SQL Server needed to leverage this platform to perform practical and effective analysis using real-world data.
SQL Server remains one of the most popular data platforms on the planet. Many industries want to leverage popular predictive models using SQL Server and recent features, enhancements, and the power of the cloud have made this more accessible than ever. In this course, Predictive Analysis with SQL Server, you'll learn how to prepare data for predictive analytics within SQL Server. First, you'll see some of the most popular methods for predictive models, such as regressions and clustering, demonstrated with hands-on demos and code samples. Next, you'll dig into analyzing the effectiveness of these queries. Finally, you'll explore optimizing the SQL Server platform for these types of analytical workloads. By the end of this course, you'll have the skills and knowledge of building a predictive model directly in SQL Server needed to leverage this platform to perform practical and effective analysis using real-world data.
