Advanced Analytics with Transact-SQL

This book serves as a comprehensive guide to leveraging T-SQL for business intelligence and data science, enhancing existing skills for effective analysis.

In Advanced Analytics with Transact-SQL, readers are introduced to the powerful features of business intelligence (BI) within T-SQL, enabling effective data science and analytics without needing to rely on additional programming languages like R or Python. The book guides you through computing essential statistical measures using your existing T-SQL skills, covering descriptive statistics such as centers, spreads, skewness, and kurtosis. It also delves into finding associations between variables, including the calculation of linear regression formulas and confidence levels through definite integration.

Data quality is a crucial aspect of any analysis, and Advanced Analytics with Transact-SQL addresses this by introducing common data quality issues. Readers will learn how to check for completeness and accuracy, as well as measure improvements in data quality over time. The book also covers optimizing queries involving temporal data, including techniques for searching overlapping intervals. More advanced topics such as hazard and survival analysis, along with forecasting using exponential moving averages and autoregression, are also explored.

The author, Dejan Sarka, emphasizes the importance of T-SQL window functions in solving many of the challenges presented in the book. Efficient statistical queries are demonstrated, optimized through creative algorithms based on mathematical principles. This comprehensive guide is ideal for database developers and administrators looking to enhance their T-SQL skills in the realm of BI and data science, ultimately making T-SQL a primary language for analytic tasks.