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Advanced Analytics with Transact-SQL: Exploring Hidden Patterns and Rules in Your Data

Learn about business intelligence (BI) features in T-SQL and how they can help you with data science and analytics efforts without the need to bring in other languages such as R and Python. This book shows you how to compute statistical measures using your existing skills in T-SQL. You will learn how to calculate descriptive statistics, including centers, spreads, skewness, and kurtosis of distributions. You will also learn to find associations between pairs of variables, including calculating linear regression formulas and confidence levels with definite integration. No analysis is good without data quality. Advanced Analytics with Transact-SQL introduces data quality issues and shows you how to check for completeness and accuracy, and measure improvements in data quality over time. The book also explains how to optimize queries involving temporal data, such as when you search for overlapping intervals. More advanced time-oriented information in the book includes hazard and survival analysis. Forecasting with exponential moving averages and autoregression is covered as well. Every web/retail shop wants to know the products customers tend to buy together. Trying to predict the target discrete or continuous variable with few input variables is important for practically every type of business. This book helps you understand data science and the advanced algorithms use to analyze data, and terms such as data mining, machine learning, and text mining. Key to many of the solutions in this book are T-SQL window functions. Author Dejan Sarka demonstrates efficient statistical queries that are based on window functions and optimized through algorithms built using mathematical knowledge and creativity. The formulas and usage of those statistical procedures are explained so you can understand and modify the techniques presented. T-SQL is supported in SQL Server,Azure SQL Database, and in Azure Synapse Analytics. There are so many BI features in T-SQL that it might become your primary analytic database language. If you want to learn how to get information from your data with the T-SQL language that you already are familiar with, then this is the book for you. What You Will Learn Describe distribution of variables with statistical measures Find associations between pairs of variables Evaluate the quality of the data you are analyzing Perform time-series analysis on your data Forecast values of a continuous variable Perform market-basket analysis to predict customer purchasing patterns Predict target variable outcomes from one or more input variables Categorize passages of text by extracting and analyzing keywords Who This Book Is For Database developers and database administrators who want to translate their T-SQL skills into the world of business intelligence (BI) and data science. For readers who want to analyze large amounts of data efficiently by using their existing knowledge of T-SQL and Microsoft’s various database platforms such as SQL Server and Azure SQL Database. Also for readers who want to improve their querying by learning new and original optimization techniques.

Mastering SQL Server 2017

Leverage the power of SQL Server 2017 Integration Services to build data integration solutions with ease Key Features Work with temporal tables to access information stored in a table at any time Get familiar with the latest features in SQL Server 2017 Integration Services Program and extend your packages to enhance their functionality Book Description Microsoft SQL Server 2017 uses the power of R and Python for machine learning and containerization-based deployment on Windows and Linux. By learning how to use the features of SQL Server 2017 effectively, you can build scalable apps and easily perform data integration and transformation. You'll start by brushing up on the features of SQL Server 2017. This Learning Path will then demonstrate how you can use Query Store, columnstore indexes, and In-Memory OLTP in your apps. You'll also learn to integrate Python code in SQL Server and graph database implementations for development and testing. Next, you'll get up to speed with designing and building SQL Server Integration Services (SSIS) data warehouse packages using SQL server data tools. Toward the concluding chapters, you'll discover how to develop SSIS packages designed to maintain a data warehouse using the data flow and other control flow tasks. By the end of this Learning Path, you'll be equipped with the skills you need to design efficient, high-performance database applications with confidence. This Learning Path includes content from the following Packt books: SQL Server 2017 Developer's Guide by Milos Radivojevic, Dejan Sarka, et. al SQL Server 2017 Integration Services Cookbook by Christian Cote, Dejan Sarka, et. al What you will learn Use columnstore indexes to make storage and performance improvements Extend database design solutions using temporal tables Exchange JSON data between applications and SQL Server Migrate historical data to Microsoft Azure by using Stretch Database Design the architecture of a modern Extract, Transform, and Load (ETL) solution Implement ETL solutions using Integration Services for both on-premise and Azure data Who this book is for This Learning Path is for database developers and solution architects looking to develop ETL solutions with SSIS, and explore the new features in SSIS 2017. Advanced analysis practitioners, business intelligence developers, and database consultants dealing with performance tuning will also find this book useful. Basic understanding of database concepts and T-SQL is required to get the best out of this Learning Path.

SQL Server 2017 Integration Services Cookbook

SQL Server 2017 Integration Services Cookbook is your key to mastering effective data integration and transformation solutions using SSIS 2017. Through clear, concise recipes, this book teaches the advanced ETL techniques necessary for creating efficient data workflows, leveraging both traditional and modern data platforms. What this Book will help me do Master the integration of diverse data sources into comprehensive data models. Develop optimized ETL workflows that improve operational efficiency. Leverage the new features introduced in SQL Server 2017 for enhanced data processing. Implement scalable data warehouse solutions suitable for modern analytics workloads. Customize and extend integration services to handle specific data transformation needs. Author(s) The authors are seasoned professionals in data integration and ETL technologies. They bring years of real-world experience using SQL Server Integration Services in various enterprise scenarios. Their combined expertise ensures practical insights and guidance, making complex concepts accessible to learners and practitioners alike. Who is it for? This book is ideal for data engineers and ETL developers who already understand the basics of SQL Server and want to master advanced data integration techniques. It is also suitable for database administrators and data analysts aiming to enhance their skill set with efficient ETL processes. Arm yourself with this guide to learn not just the how, but also the why, behind successful data transformations.

SQL Server 2016 Developer's Guide

SQL Server 2016 Developer's Guide provides an in-depth overview of the new features and enhancements introduced in SQL Server 2016 that can significantly improve your development process. This book covers robust techniques for building high-performance, secure database applications while leveraging cutting-edge functionalities such as Stretch Database, temporal tables, and enhanced In-Memory OLTP capabilities. What this Book will help me do Master the new development features introduced in SQL Server 2016 and understand their applications. Use In-Memory OLTP enhancements to significantly boost application performance. Efficiently manage and analyze data using temporal tables and JSON integration. Explore SQL Server security enhancements to ensure data safety and access control. Gain insights into integrating R with SQL Server 2016 for advanced analytics. Author(s) None Radivojević, Dejan Sarka, and William Durkin are experienced database developers and architects with a strong focus on SQL Server technologies. They bring years of practical experience and a clear, insightful approach to teaching complex concepts. Their expertise shines in this comprehensive guide, providing readers with both foundational knowledge and advanced techniques. Who is it for? This guide is perfect for database developers and solution architects looking to harness the full potential of SQL Server 2016's new features. It's intended for professionals with prior experience in SQL Server or similar platforms who aim to develop efficient, high-performance applications. You'll benefit from this book if you are keen to master SQL Server 2016 and elevate your development skills.

Training Kit (Exam 70-463): Implementing a Data Warehouse with Microsoft SQL Server 2012

Ace your preparation for Microsoft® Certification Exam 70-463 with this 2-in-1 Training Kit from Microsoft Press®. Work at your own pace through a series of lessons and practical exercises, and then assess your skills with online practice tests—featuring multiple, customizable testing options. Maximize your performance on the exam by learning how to: Design and implement a data warehouse Develop and enhance SQL Server Integration Services packages Manage and maintain SQL Server Integration Services packages Build data quality solutions Implement custom code in SQL Server Integration Services packages