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SQL Server 2017 Developer’s Guide

SQL Server 2017 Developer’s Guide PDF Author: William Durkin
Publisher: Packt Publishing Ltd
ISBN: 1788479939
Category : Computers
Languages : en
Pages : 816
Book Description
Build smarter and efficient database application systems for your organization with SQL Server 2017 Key Features Build database applications by using the development features of SQL Server 2017 Work with temporal tables to get information stored in a table at any time Use adaptive querying to enhance the performance of your queries Book Description Microsoft SQL Server 2017 is the next big step in the data platform history of Microsoft as it brings in the power of R and Python for machine learning and containerization-based deployment on Windows and Linux. Compared to its predecessor, SQL Server 2017 has evolved into Machine Learning with R services for statistical analysis and Python packages for analytical processing. This book prepares you for more advanced topics by starting with a quick introduction to SQL Server 2017’s new features and a recapitulation of the possibilities you may have already explored with previous versions of SQL Server. The next part introduces you to enhancements in the Transact-SQL language and new database engine capabilities and then switches to a completely new technology inside SQL Server: JSON support. We also take a look at the Stretch database, security enhancements, and temporal tables. Furthermore, the book focuses on implementing advanced topics, including Query Store, columnstore indexes, and In-Memory OLTP. Towards the end of the book, you’ll be introduced to R and how to use the R language with Transact-SQL for data exploration and analysis. You’ll also learn to integrate Python code in SQL Server and graph database implementations along with deployment options on Linux and SQL Server in containers for development and testing. By the end of this book, you will have the required information to design efficient, high-performance database applications without any hassle. What you will learn Explore the new development features introduced in SQL Server 2017 Identify opportunities for In-Memory OLTP technology Use columnstore indexes to get storage and performance improvements Exchange JSON data between applications and SQL Server Use the new security features to encrypt or mask the data Control the access to the data on the row levels Discover the potential of R and Python integration Model complex relationships with the graph databases in SQL Server 2017 Who this book is for Database developers and solution architects looking to design efficient database applications using SQL Server 2017 will find this book very useful. In addition, this book will be valuable to advanced analysis practitioners and business intelligence developers. Database consultants dealing with performance tuning will get a lot of useful information from this book as well. Some basic understanding of database concepts and T-SQL is required to get the best out of this book.

SQL Server 2017 Developer’s Guide

SQL Server 2017 Developer’s Guide PDF Author: William Durkin
Publisher: Packt Publishing Ltd
ISBN: 1788479939
Category : Computers
Languages : en
Pages : 816
Book Description
Build smarter and efficient database application systems for your organization with SQL Server 2017 Key Features Build database applications by using the development features of SQL Server 2017 Work with temporal tables to get information stored in a table at any time Use adaptive querying to enhance the performance of your queries Book Description Microsoft SQL Server 2017 is the next big step in the data platform history of Microsoft as it brings in the power of R and Python for machine learning and containerization-based deployment on Windows and Linux. Compared to its predecessor, SQL Server 2017 has evolved into Machine Learning with R services for statistical analysis and Python packages for analytical processing. This book prepares you for more advanced topics by starting with a quick introduction to SQL Server 2017’s new features and a recapitulation of the possibilities you may have already explored with previous versions of SQL Server. The next part introduces you to enhancements in the Transact-SQL language and new database engine capabilities and then switches to a completely new technology inside SQL Server: JSON support. We also take a look at the Stretch database, security enhancements, and temporal tables. Furthermore, the book focuses on implementing advanced topics, including Query Store, columnstore indexes, and In-Memory OLTP. Towards the end of the book, you’ll be introduced to R and how to use the R language with Transact-SQL for data exploration and analysis. You’ll also learn to integrate Python code in SQL Server and graph database implementations along with deployment options on Linux and SQL Server in containers for development and testing. By the end of this book, you will have the required information to design efficient, high-performance database applications without any hassle. What you will learn Explore the new development features introduced in SQL Server 2017 Identify opportunities for In-Memory OLTP technology Use columnstore indexes to get storage and performance improvements Exchange JSON data between applications and SQL Server Use the new security features to encrypt or mask the data Control the access to the data on the row levels Discover the potential of R and Python integration Model complex relationships with the graph databases in SQL Server 2017 Who this book is for Database developers and solution architects looking to design efficient database applications using SQL Server 2017 will find this book very useful. In addition, this book will be valuable to advanced analysis practitioners and business intelligence developers. Database consultants dealing with performance tuning will get a lot of useful information from this book as well. Some basic understanding of database concepts and T-SQL is required to get the best out of this book.

Mastering SQL Server 2017

Mastering SQL Server 2017 PDF Author: Miloš Radivojević
Publisher: Packt Publishing Ltd
ISBN: 1838987525
Category : Computers
Languages : en
Pages : 696
Book Description
Leverage the power of SQL Server 2017 Integration Services to build data integration solutions with ease Key FeaturesWork with temporal tables to access information stored in a table at any timeGet familiar with the latest features in SQL Server 2017 Integration ServicesProgram and extend your packages to enhance their functionalityBook 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 Miloš Radivojević, Dejan Sarka, et. al SQL Server 2017 Integration Services Cookbook by Christian Cote, Dejan Sarka, et. alWhat you will learnUse columnstore indexes to make storage and performance improvementsExtend database design solutions using temporal tablesExchange JSON data between applications and SQL ServerMigrate historical data to Microsoft Azure by using Stretch DatabaseDesign the architecture of a modern Extract, Transform, and Load (ETL) solutionImplement ETL solutions using Integration Services for both on-premise and Azure dataWho 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.

Data Science with SQL Server Quick Start Guide

Data Science with SQL Server Quick Start Guide PDF Author: Dejan Sarka
Publisher: Packt Publishing Ltd
ISBN: 1789537134
Category : Computers
Languages : en
Pages : 206
Book Description
Get unique insights from your data by combining the power of SQL Server, R and Python Key Features Use the features of SQL Server 2017 to implement the data science project life cycle Leverage the power of R and Python to design and develop efficient data models find unique insights from your data with powerful techniques for data preprocessing and analysis Book Description SQL Server only started to fully support data science with its two most recent editions. If you are a professional from both worlds, SQL Server and data science, and interested in using SQL Server and Machine Learning (ML) Services for your projects, then this is the ideal book for you. This book is the ideal introduction to data science with Microsoft SQL Server and In-Database ML Services. It covers all stages of a data science project, from businessand data understanding,through data overview, data preparation, modeling and using algorithms, model evaluation, and deployment. You will learn to use the engines and languages that come with SQL Server, including ML Services with R and Python languages and Transact-SQL. You will also learn how to choose which algorithm to use for which task, and learn the working of each algorithm. What you will learn Use the popular programming languages,T-SQL, R, and Python, for data science Understand your data with queries and introductory statistics Create and enhance the datasets for ML Visualize and analyze data using basic and advanced graphs Explore ML using unsupervised and supervised models Deploy models in SQL Server and perform predictions Who this book is for SQL Server professionals who want to start with data science, and data scientists who would like to start using SQL Server in their projects will find this book to be useful. Prior exposure to SQL Server will be helpful.

SQL Server 2016 Developer's Guide

SQL Server 2016 Developer's Guide PDF Author: Dejan Sarka
Publisher: Packt Publishing Ltd
ISBN: 1786460742
Category : Computers
Languages : en
Pages : 616
Book Description
Get the most out of the rich development capabilities of SQL Server 2016 to build efficient database applications for your organization About This Book Utilize the new enhancements in Transact-SQL and security features in SQL Server 2016 to build efficient database applications Work with temporal tables to get information about data stored in the table at any point in time A detailed guide to SQL Server 2016, introducing you to multiple new features and enhancements to improve your overall development experience Who This Book Is For This book is for database developers and solution architects who plan to use the new SQL Server 2016 features for developing efficient database applications. It is also ideal for experienced SQL Server developers who want to switch to SQL Server 2016 for its rich development capabilities. Some understanding of the basic database concepts and Transact-SQL language is assumed. What You Will Learn Explore the new development features introduced in SQL Server 2016 Identify opportunities for In-Memory OLTP technology, significantly enhanced in SQL Server 2016 Use columnstore indexes to get significant storage and performance improvements Extend database design solutions using temporal tables Exchange JSON data between applications and SQL Server in a more efficient way Migrate historical data transparently and securely to Microsoft Azure by using Stretch Database Use the new security features to encrypt or to have more granular control over access to rows in a table Simplify performance troubleshooting with Query Store Discover the potential of R's integration with SQL Server In Detail Microsoft SQL Server 2016 is considered the biggest leap in the data platform history of the Microsoft, in the ongoing era of Big Data and data science. Compared to its predecessors, SQL Server 2016 offers developers a unique opportunity to leverage the advanced features and build applications that are robust, scalable, and easy to administer. This book introduces you to new features of SQL Server 2016 which will open a completely new set of possibilities for you as a developer. It prepares you for the more advanced topics by starting with a quick introduction to SQL Server 2016's new features and a recapitulation of the possibilities you may have already explored with previous versions of SQL Server. The next part introduces you to small delights in the Transact-SQL language and then switches to a completely new technology inside SQL Server - JSON support. We also take a look at the Stretch database, security enhancements, and temporal tables. The last chapters concentrate on implementing advanced topics, including Query Store, columnstore indexes, and In-Memory OLTP. You will finally be introduced to R and how to use the R language with Transact-SQL for data exploration and analysis. By the end of this book, you will have the required information to design efficient, high-performance database applications without any hassle. Style and approach This book is a detailed guide to mastering the development features offered by SQL Server 2016, with a unique learn-as-you-do approach. All the concepts are explained in a very easy-to-understand manner and are supplemented with examples to ensure that you—the developer—are able to take that next step in building more powerful, robust applications for your organization with ease.

The SQL Server DBA’s Guide to Docker Containers

The SQL Server DBA’s Guide to Docker Containers PDF Author: Edwin M Sarmiento
Publisher: Apress
ISBN: 1484258266
Category : Computers
Languages : en
Pages : 362
Book Description
Get introduced to the world of Docker containers from a SQL Server DBA’s perspective. This book explains container technology and how it can improve the deployment of your SQL Server databases without infrastructure lock-in. You will be equipped with the right technical skills to guide stakeholders in your business as they adopt and adapt to new technologies to improve time-to-market and competitiveness. You will learn how to build a lab environment at home on which to build skills that transfer directly into your day job. This book teaches you how to install and configure Docker on both Windows Server and Linux operating systems. You will learn the most common Docker commands that you need to know as a DBA to deploy and manage SQL Server on containers. Support for SQL Server on Linux is new, and this book has your back with guidance on creating Docker images specifically for deployment to a Linux platform. Included is coverage of key Linux commands needed to manage SQL Server on that operating system. By the end of the book you will have learned how to create your own custom SQL Server container images with configuration settings that are specific to your organization, that are capable of being deployed to both Windows Server and Linux. What You Will LearnCreate Docker containers for agile deployment of SQL ServerRun multiple SQL Server instances on a single Linux machineDeploy custom images specific to your organization’s needsKnow the benefits and architecture of container technologyInstall and configure Docker on Windows Server and Linux Manage and persist SQL Server data in Docker containers Who This Book Is For Intermediate to senior SQL Server DBAs who are familiar with SQL Server on Windows and want to build their existing skills to deploy and manage SQL Server on Linux and through Docker containers. Readers should have a grasp of relational database concepts and be comfortable with the Transact-SQL language.

Microsoft Certified Azure Data Fundamentals Study Guide

Microsoft Certified Azure Data Fundamentals Study Guide PDF Author: Jake Switzer
Publisher: John Wiley & Sons
ISBN: 1119855845
Category : Computers
Languages : en
Pages : 400
Book Description
The most authoritative and complete study guide for people beginning to work with data in the Azure cloud In MC Azure Data Fundamentals Study Guide: Exam DP-900, expert Cloud Solution Architect Jake Switzer delivers a hands-on blueprint to acing the DP-900 Azure data certification. The book prepares you for the test – and for a new career in Azure data analytics, architecture, science, and more – with a laser-focus on the job roles and responsibilities of Azure data professionals. You’ll receive a foundational knowledge of core data concepts, like relational and non-relational data and transactional and analytical data workloads, while diving deep into every competency covered on the DP-900 exam. You’ll also get: Access to complimentary online study tools, including hundreds of practice exam questions, electronic flashcards, and a searchable glossary Additional prep assistance with access to Sybex’s superior interactive online learning environment and test bank Walkthroughs of skills and knowledge that are absolutely necessary for current and aspiring Azure data pros in introductory roles Perfect for anyone just beginning to work with data in the cloud, MC Azure Data Fundamentals Study Guide: Exam DP-900 is a can’t-miss resource for anyone prepping for the DP-900 exam or considering a new career working with Azure data.

Data Modeling for Azure Data Services

Data Modeling for Azure Data Services PDF Author: Peter ter Braake
Publisher: Packt Publishing Ltd
ISBN: 1801076707
Category : Computers
Languages : en
Pages : 428
Book Description
Choose the right Azure data service and correct model design for successful implementation of your data model with the help of this hands-on guide Key Features Design a cost-effective, performant, and scalable database in Azure Choose and implement the most suitable design for a database Discover how your database can scale with growing data volumes, concurrent users, and query complexity Book Description Data is at the heart of all applications and forms the foundation of modern data-driven businesses. With the multitude of data-related use cases and the availability of different data services, choosing the right service and implementing the right design becomes paramount to successful implementation. Data Modeling for Azure Data Services starts with an introduction to databases, entity analysis, and normalizing data. The book then shows you how to design a NoSQL database for optimal performance and scalability and covers how to provision and implement Azure SQL DB, Azure Cosmos DB, and Azure Synapse SQL Pool. As you progress through the chapters, you'll learn about data analytics, Azure Data Lake, and Azure SQL Data Warehouse and explore dimensional modeling, data vault modeling, along with designing and implementing a Data Lake using Azure Storage. You'll also learn how to implement ETL with Azure Data Factory. By the end of this book, you'll have a solid understanding of which Azure data services are the best fit for your model and how to implement the best design for your solution. What you will learn Model relational database using normalization, dimensional, or Data Vault modeling Provision and implement Azure SQL DB and Azure Synapse SQL Pools Discover how to model a Data Lake and implement it using Azure Storage Model a NoSQL database and provision and implement an Azure Cosmos DB Use Azure Data Factory to implement ETL/ELT processes Create a star schema model using dimensional modeling Who this book is for This book is for business intelligence developers and consultants who work on (modern) cloud data warehousing and design and implement databases. Beginner-level knowledge of cloud data management is expected.

High-Performance Computing Systems and Technologies in Scientific Research, Automation of Control and Production

High-Performance Computing Systems and Technologies in Scientific Research, Automation of Control and Production PDF Author: Vladimir Jordan
Publisher: Springer Nature
ISBN: 3030941418
Category : Automatic control
Languages : en
Pages : 428
Book Description
This book constitutes selected revised and extended papers from the 11th International Conference on High-Performance Computing Systems and Technologies in Scientific Research, Automation of Control and Production, HPCST 2021, Barnaul, Russia, in May 2021. The 32 full papers presented in this volume were thoroughly reviewed and selected form 98 submissions. The papers are organized in topical sections on Hardware for High-Performance Computing and Signal Processing; Information Technologies and Computer Simulation of Physical Phenomena; Computing Technologies in Discrete Mathematics and Decision Making; Information and Computing Technologies in Automation and Control Science; and Computing Technologies in Information Security Applications.

Administering and Developing SQL Server 2017 for Linux

Administering and Developing SQL Server 2017 for Linux PDF Author: Agus Kurniawan
Publisher: PE Press
ISBN:
Category : Computers
Languages : en
Pages :
Book Description
This is a basic book to explain how to deploy and manage SQL Server 2017 on Linux. The following is a list of topic that covers in this book: * Preparing System Environment * Administering SQL Server 2017 on Linux * Developing Applications for SQL Server 2017 on Linux * SQL Server Integration Services (SSIS) * Backup and Restore * Azure SQL Server 2017 on Linux

Human Capital Systems, Analytics, and Data Mining

Human Capital Systems, Analytics, and Data Mining PDF Author: Robert C. Hughes
Publisher: CRC Press
ISBN: 1498764797
Category : Business & Economics
Languages : en
Pages : 272
Book Description
Human Capital Systems, Analytics, and Data Mining provides human capital professionals, researchers, and students with a comprehensive and portable guide to human capital systems, analytics and data mining. The main purpose of this book is to provide a rich tool set of methods and tutorials for Human Capital Management Systems (HCMS) database modeling, analytics, interactive dashboards, and data mining that is independent of any human capital software vendor offerings and is equally usable and portable among both commercial and internally developed HCMS. The book begins with an overview of HCMS, including coverage of human resource systems history and current HCMS Computing Environments. It next explores relational and dimensional database management concepts and principles. HCMS Instructional databases developed by the Author for use in Graduate Level HCMS and Compensation Courses are used for database modeling and dashboard design exercises. Exciting knowledge discovery and research Tutorials and Exercises using Online Analytical Processing (OLAP) and data mining tools through replication of actual original pay equity research by the author are included. New findings concerning Gender Based Pay Equity Research through the lens Comparable Worth and Occupational Mobility are covered extensively in Human Capital Metrics, Analytics and Data Mining Chapters.