Run queries and analysis on big data clusters across relational and non relational databases Ê KEY FEATURESÊÊ _ Connect to Hadoop, Azure, Spark, Oracle, Teradata, Cassandra, MongoDB, CosmosDB, MySQL, PostgreSQL, MariaDB, and SAP HANA. _ Numerous techniques on how to query data and troubleshoot Polybase for better data analytics. _ Exclusive coverage on Azure Synapse Analytics and building Big Data clusters. DESCRIPTIONÊ This book brings exciting coverage on establishing and managing data virtualization using polybase. This book teaches how to configure polybase on almost all relational and nonrelational databases. You will learn to set up the test environment for any tool or software instantly without hassle. You will practice how to design and build some of the high performing data warehousing solutions and that too in a few minutes of time. You will almost become an expert in connecting to all databases including hadoop, cassandra, MySQL, PostgreSQL, MariaDB and Oracle database. This book also brings exclusive coverage on how to build data clusters on Azure and using Azure Synapse Analytics. By the end of this book, you just don't administer the polybase for managing big data clusters but rather you learn to optimize and boost the performance for enabling data analytics and ease of data accessibility. WHAT YOU WILL LEARN _ Learn to configure Polybase and process Transact SQL queries with ease. _ Create a Docker container with SQL Server 2019 on Windows and Polybase. _ Establish SQL Server instance with any other software or tool using Polybase _ Connect with Cassandra, MongoDB, MySQL, PostgreSQL, MariaDB, and IBM DB2. WHO THIS BOOK IS FORÊÊ This book is for database developers and administrators familiar with the SQL language and command prompt. Managers and decision-makers will also find this book useful. No prior knowledge of any other technology or language is required. TABLE OF CONTENTS 1. What is Data Virtualization (Polybase) 2. History of Polybase 3. Polybase current state 4. Differences with other technologies 5. Usage 6. Future 7. SQL Server 8. Hadoop Cloudera and Hortonworks 9. Windows Azure Storage Blob 10. Spark 11. From Azure Synapse Analytics 12. From Big Data Clusters 13. Oracle 14. Teradata 15. Cassandra 16. MongoDB 17. CosmosDB 18. MySQL 19. PostgreSQL 20. MariaDB 21. SAP HANA 22. IBM DB2 23. Excel

Get up to speed with the new features added to Microsoft SQL Server 2019 Analysis Services and create models to support your business Key FeaturesExplore tips and tricks to design, develop, and optimize end-to-end data analytics solutions using Microsoft's technologiesLearn tabular modeling and multi-dimensional cube design development using real-world examplesImplement Analysis Services to help you make productive business decisionsBook Description SQL Server Analysis Services (SSAS) continues to be a leading enterprise-scale toolset, enabling customers to deliver data and analytics across large datasets with great performance. This book will help you understand MS SQL Server 2019’s new features and improvements, especially when it comes to SSAS. First, you’ll cover a quick overview of SQL Server 2019, learn how to choose the right analytical model to use, and understand their key differences. You’ll then explore how to create a multi-dimensional model with SSAS and expand on that model with MDX. Next, you’ll create and deploy a tabular model using Microsoft Visual Studio and Management Studio. You'll learn when and how to use both tabular and multi-dimensional model types, how to deploy and configure your servers to support them, and design principles that are relevant to each model. The book comes packed with tips and tricks to build measures, optimize your design, and interact with models using Excel and Power BI. All this will help you visualize data to gain useful insights and make better decisions. Finally, you’ll discover practices and tools for securing and maintaining your models once they are deployed. By the end of this MS SQL Server book, you’ll be able to choose the right model and build and deploy it to support the analytical needs of your business. What you will learnDetermine the best analytical model using SSASCover the core aspects involved in MDX, including writing your first queryImplement calculated tables and calculation groups (new in version 2019) in DAXCreate and deploy tabular and multi-dimensional models on SQL 2019Connect and create data visualizations using Excel and Power BIImplement row-level and other data security methods with tabular and multi-dimensional modelsExplore essential concepts and techniques to scale, manage, and optimize your SSAS solutionsWho this book is for This Microsoft SQL Server book is for BI professionals and data analysts who are looking for a practical guide to creating and maintaining tabular and multi-dimensional models using SQL Server 2019 Analysis Services. A basic working knowledge of BI solutions such as Power BI and database querying is required.

Harness the power of PolyBase data virtualization software to make data from a variety of sources easily accessible through SQL queries while using the T-SQL skills you already know and have mastered. PolyBase Revealed shows you how to use the PolyBase feature of SQL Server 2019 to integrate SQL Server with Azure Blob Storage, Apache Hadoop, other SQL Server instances, Oracle, Cosmos DB, Apache Spark, and more. You will learn how PolyBase can help you reduce storage and other costs by avoiding the need for ETL processes that duplicate data in order to make it accessible from one source. PolyBase makes SQL Server into that one source, and T-SQL is your golden ticket. The book also covers PolyBase scale-out clusters, allowing you to distribute PolyBase queries among several SQL Server instances, thus improving performance. With great flexibility comes great complexity, and this book shows you where to look when queries fail, complete with coverage of internals, troubleshooting techniques, and where to find more information on obscure cross-platform errors. Data virtualization is a key target for Microsoft with SQL Server 2019. This book will help you keep your skills current, remain relevant, and build new business and career opportunities around Microsoft’s product direction. What You Will LearnInstall and configure PolyBase as a stand-alone service, or unlock its capabilities with a scale-out cluster Understand how PolyBase interacts with outside data sources while presenting their data as regular SQL Server tables Write queries combining data from SQL Server, Apache Hadoop, Oracle, Cosmos DB, Apache Spark, and more Troubleshoot PolyBase queries using SQL Server Dynamic Management Views Tune PolyBase queries using statistics and execution plans Solve common business problems, including "cold storage" of infrequently accessed data and simplifying ETL jobs Who This Book Is For SQL Server developers working in multi-platform environments who want one easy way of communicating with, and collecting data from, all of these sources

Explore and work with various Microsoft Azure services for real-time Data Analytics KEY FEATURESÊ Understanding what Azure can do with your data Understanding the analytics services offered by Azure Understand how data can be transformed to generate more data Understand what is done after a Machine Learning model is builtÊ Go through some Data Analytics real-world use cases ÊÊ DESCRIPTIONÊ Data is the key input for Analytics. Building and implementing data platforms such as Data Lakes, modern Data Marts, and Analytics at scale require the right cloud platform that Azure provides through its services. The book starts by sharing how analytics has evolved and continues to evolve. Following the introduction, you will deep dive into ingestion technologies. You will learn about Data processing services in Azure. You will next learn about what is meant by a Data Lake and understand how Azure Data Lake Storage is used for analytical workloads. You will then learn about critical services that will provide actual Machine Learning capabilities in Azure. The book also talks about Azure Data Catalog for cataloging, Azure AD for Access Management, Web Apps and PowerApps for cloud web applications, Cognitive services for Speech, Vision, Search and Language, Azure VM for computing and Data Science VMs, Functions as serverless computing, Kubernetes and Containers as deployment options. Towards the end, the book discusses two use cases on Analytics. WHAT WILL YOU LEARNÊÊ Explore and work with various Azure services Orchestrate and ingest data using Azure Data Factory Learn how to use Azure Stream Analytics Get to know more about Synapse Analytics and its features Learn how to use Azure Analysis Services and its functionalities Ê WHO THIS BOOK IS FORÊ This book is for anyone who has basic to intermediate knowledge of cloud and analytics concepts and wants to use Microsoft Azure for Data Analytics. This book will also benefit Data Scientists who want to use Azure for Machine Learning. Ê TABLE OF CONTENTSÊÊ 1. Ê Data and its power 2. Ê Evolution of Analytics and its Types 3. Ê Internet of Things 4. Ê AI and ML 5. Ê Why cloud 6. Ê What are a data lake and a modern datamart 7. Ê Introduction to Azure services 8. Ê Types of data 9. Ê Azure Data Factory 10. Stream Analytics 11. Azure Data Lake Store and Azure Storage 12. Cosmos DB 13.Ê Synapse Analytics 14.Ê Azure Databricks 15.Ê Azure Analysis Services 16.Ê Power BI 17.Ê Azure Machine Learning 18.Ê Sample Architectures and synergies - Real-Time and Batch 19.Ê Azure Data Catalog 20.Ê Azure Active Directory 21.Ê Azure Webapps 22.Ê Power apps 23.Ê Time Series Insights 24.Ê Azure Cognitive Services 25.Ê Azure Logicapps 26.Ê Azure VM 27.Ê Azure Functions 28.Ê Azure Containers 29.Ê Azure KubernetesÊ Service 30.Ê Use Case 1 31.Ê Use Case 2

Get a head-start on learning one of SQL Server 2019’s latest and most impactful features—Big Data Clusters—that combines large volumes of non-relational data for analysis along with data stored relationally inside a SQL Server database. This book provides a first look at Big Data Clusters based upon SQL Server 2019 Release Candidate 1. Start now and get a jump on your competition in learning this important new feature. Big Data Clusters is a feature set covering data virtualization, distributed computing, and relational databases and provides a complete AI platform across the entire cluster environment. This book shows you how to deploy, manage, and use Big Data Clusters. For example, you will learn how to combine data stored on the HDFS file system together with data stored inside the SQL Server instances that make up the Big Data Cluster. Filled with clear examples and use cases, this book provides everything necessary to get started working with Big Data Clusters in SQL Server 2019 using Release Candidate 1. You will learn about the architectural foundations that are made up from Kubernetes, Spark, HDFS, and SQL Server on Linux. You then are shown how to configure and deploy Big Data Clusters in on-premises environments or in the cloud. Next, you are taught about querying. You will learn to write queries in Transact-SQL—taking advantage of skills you have honed for years—and with those queries you will be able to examine and analyze data from a wide variety of sources such as Apache Spark. Through the theoretical foundation provided in this book and easy-to-follow example scripts and notebooks, you will be ready to use and unveil the full potential of SQL Server 2019: combining different types of data spread across widely disparate sources into a single view that is useful for business intelligence and machine learning analysis. What You Will LearnInstall, manage, and troubleshoot Big Data Clusters in cloud or on-premise environments Analyze large volumes of data directly from SQL Server and/or Apache Spark Manage data stored in HDFS from SQL Server as if it were relational data Implement advanced analytics solutions through machine learning and AI Expose different data sources as a single logical source using data virtualization Who This Book Is For For data engineers, data scientists, data architects, and database administrators who want to employ data virtualization and big data analytics in their environment

Get up to speed on the game-changing developments in SQL Server 2019. No longer just a database engine, SQL Server 2019 is cutting edge with support for machine learning (ML), big data analytics, Linux, containers, Kubernetes, Java, and data virtualization to Azure. This is not a book on traditional database administration for SQL Server. It focuses on all that is new for one of the most successful modernized data platforms in the industry. It is a book for data professionals who already know the fundamentals of SQL Server and want to up their game by building their skills in some of the hottest new areas in technology. SQL Server 2019 Revealed begins with a look at the project's team goal to integrate the world of big data with SQL Server into a major product release. The book then dives into the details of key new capabilities in SQL Server 2019 using a “learn by example” approach for Intelligent Performance, security, mission-critical availability, and features for the modern developer. Also covered are enhancements to SQL Server 2019 for Linux and gain a comprehensive look at SQL Server using containers and Kubernetes clusters. The book concludes by showing you how to virtualize your data access with Polybase to Oracle, MongoDB, Hadoop, and Azure, allowing you to reduce the need for expensive extract, transform, and load (ETL) applications. You will then learn how to take your knowledge of containers, Kubernetes, and Polybase to build a comprehensive solution called Big Data Clusters, which is a marquee feature of 2019. You will also learn how to gain access to Spark, SQL Server, and HDFS to build intelligence over your own data lake and deploy end-to-end machine learning applications. What You Will LearnImplement Big Data Clusters with SQL Server, Spark, and HDFS Create a Data Hub with connections to Oracle, Azure, Hadoop, and other sourcesCombine SQL and Spark to build a machine learning platform for AI applicationsBoost your performance with no application changes using Intelligent PerformanceIncrease security of your SQL Server through Secure Enclaves and Data ClassificationMaximize database uptime through online indexing and Accelerated Database RecoveryBuild new modern applications with Graph, ML Services, and T-SQL Extensibility with JavaImprove your ability to deploy SQL Server on Linux Gain in-depth knowledge to run SQL Server with containers and KubernetesKnow all the new database engine features for performance, usability, and diagnosticsUse the latest tools and methods to migrate your database to SQL Server 2019Apply your knowledge of SQL Server 2019 to Azure Who This Book Is For IT professionals and developers who understand the fundamentals of SQL Server and wish to focus on learning about the new, modern capabilities of SQL Server 2019. The book is for those who want to learn about SQL Server 2019 and the new Big Data Clusters and AI feature set, support for machine learning and Java, how to run SQL Server with containers and Kubernetes, and increased capabilities around Intelligent Performance, advanced security, and high availability.

Learn how to combine SQL Server's analytics with Azure's flexibility and hybrid connectivity to achieve industry-leading performance and manageability for your cloud database. Key FeaturesUnderstand platform availability for SQL Server in AzureExplore the benefits and deployment choices offered by SQL IaaSGet to grips with deploying SQL Server on the Linux development ecosystemBook Description Deploying SQL Server on Azure virtual machines allows you to work on full versions of SQL Server in the cloud without having to maintain on-premises hardware. The book begins by introducing you to the SQL portfolio in Azure and takes you through SQL Server IaaS scenarios, before explaining the factors that you need to consider while choosing an OS for SQL Server in Azure VMs. As you progress through the book, you'll explore different VM options and deployment choices for IaaS and understand platform availability, migration tools, and best practices in Azure. In later chapters, you'll learn how to configure storage to achieve optimized performance. Finally, you'll get to grips with the concept of Azure Hybrid Benefit and find out how you can use it to maximize the value of your existing on-premises SQL Server. By the end of this book, you'll be proficient in administering SQL Server on Microsoft Azure and leveraging the tools required for its deployment. What you will learnChoose an operating system for SQL Server in Azure VMsUse the Azure Management Portal to facilitate the deployment processVerify connectivity and network latency in cloudConfigure storage for optimal performance and connectivityExplore various disaster recovery options for SQL Server in AzureOptimize SQL Server on LinuxDiscover how to back up databases to a URLWho this book is for SQL Server on Azure VMs is for you if you are a developer, data enthusiast, or anyone who wants to migrate SQL Server databases to Azure virtual machines. Basic familiarity with SQL Server and managed identities for Azure resources will be a plus.