Analytic Sql In Sql Server 2014 2016

Business Intelligence (BI) has emerged as a field which seeks to support managers in decision-making. It encompasses the techniques, methods and tools for conducting analytically-based IT solutions, which are referred to as OLAP (OnLine Analytical Processing). Within this field, SQL has a role as a leader and is continuously evolving to cover both transactional and analytical data management. This book discusses the functions provided by Microsoft® SQL Server 2014/2016 in terms of business intelligence. The analytic functions are considered as an enrichment of the SQL language. They combine a series of practical functions to answer complex analysis requests with all the simplicity, elegance and acquired performance of the SQL language. Drawing on the wide experience of the author in teaching and research, as well as insights from contacts in the industry, this book focuses on the issues and difficulties faced by academics (students and teachers) and professionals engaged in data analysis with the SQL Server 2014/2016 database management system.

Business Intelligence (BI) has emerged as a field which seeks to support managers in decision-making. It encompasses the techniques, methods and tools for conducting analytically-based IT solutions, which are referred to as OLAP (OnLine Analytical Processing). Within this field, SQL has a role as a leader and is continuously evolving to cover both transactional and analytical data management. This book discusses the functions provided by Microsoft® SQL Server 2014/2016 in terms of business intelligence. The analytic functions are considered as an enrichment of the SQL language. They combine a series of practical functions to answer complex analysis requests with all the simplicity, elegance and acquired performance of the SQL language. Drawing on the wide experience of the author in teaching and research, as well as insights from contacts in the industry, this book focuses on the issues and difficulties faced by academics (students and teachers) and professionals engaged in data analysis with the SQL Server 2014/2016 database management system.

Build agile and responsive business intelligence solutions Create a semantic model and analyze data using the tabular model in SQL Server 2016 Analysis Services to create corporate-level business intelligence (BI) solutions. Led by two BI experts, you will learn how to build, deploy, and query a tabular model by following detailed examples and best practices. This hands-on book shows you how to use the tabular model’s in-memory database to perform rapid analytics—whether you are new to Analysis Services or already familiar with its multidimensional model. Discover how to: • Determine when a tabular or multidimensional model is right for your project • Build a tabular model using SQL Server Data Tools in Microsoft Visual Studio 2015 • Integrate data from multiple sources into a single, coherent view of company information • Choose a data-modeling technique that meets your organization’s performance and usability requirements • Implement security by establishing administrative and data user roles • Define and implement partitioning strategies to reduce processing time • Use Tabular Model Scripting Language (TMSL) to execute and automate administrative tasks • Optimize your data model to reduce the memory footprint for VertiPaq • Choose between in-memory (VertiPaq) and pass-through (DirectQuery) engines for tabular models • Select the proper hardware and virtualization configurations • Deploy and manipulate tabular models from C# and PowerShell using AMO and TOM libraries Get code samples, including complete apps, at: https://aka.ms/tabular/downloads About This Book • For BI professionals who are new to SQL Server 2016 Analysis Services or already familiar with previous versions of the product, and who want the best reference for creating and maintaining tabular models. • Assumes basic familiarity with database design and business analytics concepts.

Become an expert who can use window functions to solve T-SQL query problems. Replace slow cursors and self-joins with queries that are easy to write and perform better. This new edition provides expanded examples, including a chapter from the world of sports, and covers the latest performance enhancements through SQL Server 2019. Window functions are useful in analytics and business intelligence reporting. They came into full blossom with SQL Server 2012, yet they are not as well known and used as often as they ought to be. This group of functions is one of the most notable developments in SQL, and this book shows how every developer and DBA can benefit from their expressive power in solving day-to-day business problems. Once you begin using window functions, such as ROW_NUMBER and LAG, you will discover many ways to use them. You will approach SQL Server queries in a different way, thinking about sets of data instead of individual rows. Your queries will run faster, be easier to write, and easier to deconstruct, maintain, and enhance in the future. Just knowing and using these functions is not enough. You also need to understand how to tune the queries. Expert T-SQL Window Functions in SQL Server clearly explains how to get the best performance. The book also covers the rare cases when older techniques are the best bet. What You Will LearnSolve complex query problems without cumbersome self-joins that run slowly and are difficult to read Create sliding windows in a result set for computing such as running totals and moving averages Return aggregate and detail data simultaneously from the same SELECT statement Compute lag and lead and other values that access data from multiple rows in a result set Understand the OVER clause syntax and how to control the window Avoid framing errors that can lead to unexpected results Who This Book Is For Anyone who writes T-SQL queries, including database administrators, developers, business analysts, and data scientists. Before reading this book, you should understand how to join tables, write WHERE clauses, and build aggregate queries.

The different facets of the sharing economy offer numerous opportunities for businesses ? particularly those that can be distinguished by their creative ideas and their ability to easily connect buyers and senders of goods and services via digital platforms. At the beginning of the growth of this economy, the advanced digital technologies generated billions of bytes of data that constitute what we call Big Data. This book underlines the facilitating role of Big Data analytics, explaining why and how data analysis algorithms can be integrated operationally, in order to extract value and to improve the practices of the sharing economy. It examines the reasons why these new techniques are necessary for businesses of this economy and proposes a series of useful applications that illustrate the use of data in the sharing ecosystem.

The concept of digital risk, which has become ubiquitous in the media, sustains a number of myths and beliefs about the digital world. This book explores the opposite view of these ideologies by focusing on digital risks as perceived by actors in their respective contexts. Perceptions and Analysis of Digital Risks identifies the different types of risks that concern actors and actually impact their daily lives, within education or various socio-professional environments. It provides an analysis of the strategies used by the latter to deal with these risks as they conduct their activities; thus making it possible to characterize the digital cultures and, more broadly, the informational cultures at work. This book offers many avenues for action in terms of educating the younger generations, training teachers and leaders, and mediating risks.

Use window functions to write simpler, better, more efficient T-SQL queries Most T-SQL developers recognize the value of window functions for data analysis calculations. But they can do far more, and recent optimizations make them even more powerful. In T-SQL Window Functions, renowned T-SQL expert Itzik Ben-Gan introduces breakthrough techniques for using them to handle many common T-SQL querying tasks with unprecedented elegance and power. Using extensive code examples, he guides you through window aggregate, ranking, distribution, offset, and ordered set functions. You’ll find a detailed section on optimization, plus an extensive collection of business solutions — including novel techniques available in no other book. Microsoft MVP Itzik Ben-Gan shows how to: • Use window functions to improve queries you previously built with predicates • Master essential SQL windowing concepts, and efficiently design window functions • Effectively utilize partitioning, ordering, and framing • Gain practical in-depth insight into window aggregate, ranking, offset, and statistical functions • Understand how the SQL standard supports ordered set functions, and find working solutions for functions not yet available in the language • Preview advanced Row Pattern Recognition (RPR) data analysis techniques • Optimize window functions in SQL Server and Azure SQL Database, making the most of indexing, parallelism, and more • Discover a full library of window function solutions for common business problems About This Book • For developers, DBAs, data analysts, data scientists, BI professionals, and power users familiar with T-SQL queries • Addresses any edition of the SQL Server 2019 database engine or later, as well as Azure SQL Database Get all code samples at: MicrosoftPressStore.com/TSQLWindowFunctions/downloads

This edited book presents scientific results of the 20th IEEE/ACIS International Conference on Software Engineering Research, Management, and Applications (SERA2022) held on May 25, 2022, in Las Vegas, USA. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the best papers from those papers accepted for presentation at the conference. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 12 of the conference’s most promising papers are then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will bring to the field of computer and information science.