In "Hands-On Data Science with SQL Server 2017," you will discover how to implement end-to-end data analysis workflows, leveraging SQL Server's robust capabilities. This book guides you through collecting, cleaning, and transforming data, querying for insights, creating compelling visualizations, and even constructing predictive models for sophisticated analytics. What this Book will help me do Grasp the essential data science processes and how SQL Server supports them. Conduct data analysis and create interactive visualizations using Power BI. Build, train, and assess predictive models using SQL Server tools. Integrate SQL Server with R, Python, and Azure for enhanced functionality. Apply best practices for managing and transforming big data with SQL Server. Author(s) Marek Chmel and Vladimír Mužný bring their extensive experience in data science and database management to this book. Marek is a seasoned database specialist with a strong background in SQL, while Vladimír is known for his instructional expertise in analytics and data manipulation. Together, they focus on providing actionable insights and practical examples tailored for data professionals. Who is it for? This book is an ideal resource for aspiring and seasoned data scientists, data analysts, and database professionals aiming to deepen their expertise in SQL Server for data science workflows. Beginners with fundamental SQL knowledge will find it a guided entry into data science applications. It is especially suited for those who aim to implement data-driven solutions in their roles while leveraging SQL's capabilities.

In the 'Redash v5 Quick Start Guide', you'll learn everything you need to master the Redash data visualization platform and confidently create compelling dashboards. This book covers how to connect to different data sources, use SQL to query data, and design and share insightful visualizations. What this Book will help me do Understand how to install, configure, and troubleshoot Redash for your data projects. Gain skills in managing user roles and permissions to ensure secure data collaboration. Learn to connect Redash to various data sources and fetch, process, and handle data. Master the creation of advanced visualizations to effectively present complex data. Develop proficiency in utilizing the Redash API for integrating programmatic interactions. Author(s) None Leibzon is a recognized expert in data visualization and Business Intelligence tools, with years of experience working with data-driven systems. Drawing from his deep practical knowledge of Redash and its applications, None has crafted this guide to be accessible and highly practical. His goal is to enable learners and professionals to unlock the power of data storytelling through intuitive and actionable visualization. Who is it for? If you're a Data Analyst, BI professional, or Data Developer with basic SQL skills, this book is tailored for you. It assumes no prior knowledge of Redash but benefits those who understand fundamental Business Intelligence concepts. Whether you're looking to create your first visualization or streamline data collaboration, this guide will help you achieve your goals.

Utilize this practical and easy-to-follow guide to modernize traditional enterprise data warehouse and business intelligence environments with next-generation big data technologies. Next-Generation Big Data takes a holistic approach, covering the most important aspects of modern enterprise big data. The book covers not only the main technology stack but also the next-generation tools and applications used for big data warehousing, data warehouse optimization, real-time and batch data ingestion and processing, real-time data visualization, big data governance, data wrangling, big data cloud deployments, and distributed in-memory big data computing. Finally, the book has an extensive and detailed coverage of big data case studies from Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard. What You’ll Learn Install Apache Kudu, Impala, and Spark to modernize enterprise data warehouse and business intelligence environments, complete with real-world, easy-to-follow examples, and practical advice Integrate HBase, Solr, Oracle, SQL Server, MySQL, Flume, Kafka, HDFS, and Amazon S3 with Apache Kudu, Impala, and Spark Use StreamSets, Talend, Pentaho, and CDAP for real-time and batch data ingestion and processing Utilize Trifacta, Alteryx, and Datameer for data wrangling and interactive data processing Turbocharge Spark with Alluxio, a distributed in-memory storage platform Deploy big data in the cloud using Cloudera Director Perform real-time data visualization and time series analysis using Zoomdata, Apache Kudu, Impala, and Spark Understand enterprise big data topics such as big data governance, metadata management, data lineage, impact analysis, and policy enforcement, and how to use Cloudera Navigator to perform common data governance tasks Implement big data use cases such as big data warehousing, data warehouse optimization, Internet of Things, real-time data ingestion and analytics, complex event processing, and scalable predictive modeling Study real-world big data case studies from innovative companies, including Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard Who This Book Is For BI and big data warehouse professionals interested in gaining practical and real-world insight into next-generation big data processing and analytics using Apache Kudu, Impala, and Spark; and those who want to learn more about other advanced enterprise topics

Dive into the world of ETL (Extract, Transform, Load) with 'Hands-On Data Warehousing with Azure Data Factory'. This book guides readers through the essential techniques for working with Azure Data Factory and SQL Server Integration Services to design, implement, and optimize ETL solutions for both on-premises and cloud data environments. What this Book will help me do Understand and utilize Azure Data Factory and SQL Server Integration Services to build ETL solutions. Design scalable and high-performance ETL architectures tailored to modern data problems. Integrate various Azure services, such as Azure Data Lake Analytics, Machine Learning, and Databricks Spark, into your workflows. Troubleshoot and optimize ETL pipelines and address common challenges in data processing. Create insightful Power BI dashboards to visualize and interact with data from your ETL workflows. Author(s) Authors None Cote, Michelle Gutzait, and Giuseppe Ciaburro bring a wealth of experience in data engineering and cloud technologies to this practical guide. Combining expertise in Azure ecosystem and hands-on Data Warehousing, they deliver actionable insights for working professionals. Who is it for? This book is crafted for software professionals working in data engineering, especially those specializing in ETL processes. Readers with a foundational knowledge of SQL Server and cloud infrastructures will benefit most. If you aspire to implement state-of-the-art ETL pipelines or enhance existing workflows with ADF and SSIS, this book is an ideal resource.

Write queries using little-known, but powerful, SQL features implemented in Oracle's database engine. You will be able to take advantage of Oracle’s power in implementing business logic, thereby maximizing return from your company’s investment in Oracle Database products. Important features and aspects of SQL covered in this book include the model clause, row pattern matching, analytic and aggregate functions, and recursive subquery factoring, just to name a few. The focus is on implementing business logic in pure SQL, with a comparison of different approaches that can be used to write SELECT statements to return results that drive good decision making and competitive action in the marketplace. This book covers features that are often not well known, and sometimes not implemented in competing products. Chapters on query transformation and logical execution order provide a grasp of the big picture in which the individual SQL features described in the other chapters are executed. Also included are a discussion on when to use the procedural capabilities from PL/SQL, and a series of examples showing different mixes of SQL features being applied in common types of queries that you are likely to encounter. What You Will Learn Gain competitive advantage from Oracle SQL Know when to step up to PL/SQL versus staying in SQL Become familiar with query transformations and join mechanics Apply the model clause and analytic functions to business intelligence queries Make use of features that are specific to Oracle Database, such as row pattern matching Understand the pros and cons of different SQL approaches to solving common query tasks Traverse hierarchies using CONNECT BY and recursive subquery factoring Who This Book Is For Database programmers withsome Oracle Database experience. The book is also for SQL developers who are moving to the Oracle Database platform or want to learn unique features of its query engine. Both audiences will learn to apply the full power of Oracle’s own SQL dialect to commonly encountered types of business questions and query challenges.

"SQL Server 2017 Developer's Guide" provides a comprehensive approach to learning and utilizing the new features introduced in SQL Server 2017. From advanced Transact-SQL to integrating R and Python into your database projects, this book equips you with the knowledge to design and develop efficient database applications tailored to modern requirements. What this Book will help me do Master new features in SQL Server 2017 to enhance database application development. Implement In-Memory OLTP and columnstore indexes for optimal performance. Utilize JSON support in SQL Server to integrate modern data formats. Leverage R and Python integration to apply advanced data analytics and machine learning. Learn Linux and container deployment options to expand SQL Server usage scenarios. Author(s) The authors of "SQL Server 2017 Developer's Guide" are industry veterans with extensive experience in database design, business intelligence, and advanced analytics. They bring a practical, hands-on writing style that helps developers apply theoretical concepts effectively. Their commitment to teaching is evident in the clear and detailed guidance provided throughout the book. Who is it for? This book is ideal for database developers and solution architects aiming to build robust database applications with SQL Server 2017. It's a valuable resource for business intelligence developers or analysts seeking to harness SQL Server 2017's advanced features. Some familiarity with SQL Server and T-SQL is recommended to fully leverage the insights provided by this book.

"Mastering Apache Solr 7.x" is your practical guide to building, advancing, and optimizing enterprise search solutions using Solr 7. With this book, you will harness the robust features of Solr, implement efficient search capabilities, and tackle complex business intelligence problems to achieve unparalleled search performance. What this Book will help me do Develop and implement efficient schemas using the Solr Schema API. Optimize enterprise search performance with advanced querying and scoring techniques. Implement fault-tolerant and distributed search systems using SolrCloud. Leverage Apache Tika for seamless data indexing and content extraction. Utilize programming languages like JavaScript, Python, and Ruby to integrate with Solr. Author(s) With years of experience in search technologies and deep expertise in Apache Solr, authors None Nair, None Mehta, and Dharmesh Vasoya bring together a wealth of knowledge in this book. Their collaborative insights equip readers to master advanced Solr features, sharing practical examples and real-world applications with a passion for clarity and efficiency. Who is it for? This book is ideal for software developers, data engineers, and database architects who aim to design and implement effective enterprise search systems. It is tailored for readers with prior experience in Apache Solr or Java programming, focusing on those eager to enhance their search solution expertise. Achieve your advanced search system goals here.

Quickly find solutions to dozens of common problems encountered while using XML and JSON features that are built into SQL Server. Content is presented in the popular problem-solution format. Look up the problem that you want to solve. Read the solution. Apply the solution directly in your own code. Problem solved! This book shows how to take advantage of XML and JSON to share data and automate tasks. JSON is commonly used to move data back and forth between the database and front-end applications, often running in a browser. This book shows all you need to know about transforming query results into JSON format, and back again. Also covered are the processes and techniques for moving data into and out of XML format for business intelligence and other purposes, such as when transferring data from a reporting system into a data warehouse, or between different database brands such as between SQL Server and Oracle. Microsoft intensively implements XML in SQL Server, and in many related products. Execution plans are generated in XML format, and this book shows you how to parse those plans and automate the detection of performance problems. The relatively new Extended Events feature writes tracing data into XML files, and the recipes in this book help in parsing those files. XML is also used in SQL Server's BI tool set, including in SSIS, SSR, and SSAS. XML is used in many configuration files, and is even behind the construction of DDL triggers. In reading this book you’ll dive deeply into the features that allow you to build and parse XML, and also JSON, which is a specific format of XML used to transmit objects in a web-friendly format between a database and its front-end applications. What You Will Learn Build XML and JSON objects in support of automation and data transfer Import and parse XML and JSON from operating system files Build appropriate indexes on XML objects to improve query performance Move data from query result sets into JSON format, and back again Automate the detection of database performance problems by querying and parsing the database’s own execution plans Replace external and manual JSON processes with SQL Server's internal, JSON functionality Who This Book Is For Database administrators, .NET developers, business intelligence developers, and other professionals who want a deep and detailed skill set around working with XML and JSON in a SQL Server database environment. Web developers will particularly find the book useful for its coverage of transforming database result sets into JSON text that can be transmitted to front-end web applications.

Prepare for Microsoft Exam 70-767–and help demonstrate your real-world mastery of skills for managing data warehouses. This exam is intended for Extract, Transform, Load (ETL) data warehouse developers who create business intelligence (BI) solutions. Their responsibilities include data cleansing as well as ETL and data warehouse implementation. The reader should have experience installing and implementing a Master Data Services (MDS) model, using MDS tools, and creating a Master Data Manager database and web application. The reader should understand how to design and implement ETL control flow elements and work with a SQL Service Integration Services package. Focus on the expertise measured by these objectives: • Design, and implement, and maintain a data warehouse • Extract, transform, and load data • Build data quality solutionsThis Microsoft Exam Ref: • Organizes its coverage by exam objectives • Features strategic, what-if scenarios to challenge you • Assumes you have working knowledge of relational database technology and incremental database extraction, as well as experience with designing ETL control flows, using and debugging SSIS packages, accessing and importing or exporting data from multiple sources, and managing a SQL data warehouse. Implementing a SQL Data Warehouse About the Exam Exam 70-767 focuses on skills and knowledge required for working with relational database technology. About Microsoft Certification Passing this exam earns you credit toward a Microsoft Certified Professional (MCP) or Microsoft Certified Solutions Associate (MCSA) certification that demonstrates your mastery of data warehouse management Passing this exam as well as Exam 70-768 (Developing SQL Data Models) earns you credit toward a Microsoft Certified Solutions Associate (MCSA) SQL 2016 Business Intelligence (BI) Development certification. See full details at: microsoft.com/learning

Walk away from old-fashioned and cumbersome query approaches and answer your business intelligence questions through simple and powerful queries built on common table expressions (CTEs) and window functions. These new features in MariaDB and MySQL help you to write queries without having to wade through a quagmire of brittle self-joins and other crazy techniques from the past. Your queries will generate correct results, be more readable and less brittle in the face of unexpected data, and you’ll be able to adapt them quickly in the face of changing business requirements. MariaDB and MySQL Common Table Expressions and Window Functions Revealed introduces and explains CTEs and window functions, newly available in MariaDB 10.2 and MySQL 8.0, and helps you understand why and how every MariaDB and MySQL database programmer should learn and apply these features in their daily work. CTEs and especially window functions enable easy solutions to many query challenges that in prior releases have been difficult and sometimes impossible to surmount. Mastering these features opens the door to query solutions that are more robust, execute faster, and are easier to maintain over time than prior solutions using older techniques. The book: Takes you step-by-step through the workings of common table expressions and window functions Provides easy-to-follow examples of the new syntax Helps you answer business questions faster and easier than ever What You'll Learn Answer business questions using simple queries that don’t break in the face of unexpected data Avoid writing queries that are a difficult-to-maintain quagmire of self-joins and nested subqueries Recognize situations that call for window functions, and learn when to use these features Reduce the need for performance-robbing self-joins Simplify and speed the execution of analytical queries Create queries that finish in seconds instead of hours Who This Book Is For Database administrators and application developers who want to quickly get up to speed on important features in MariaDB and MySQL for writing business intelligence queries. Any developer writing SQL against MariaDB and MySQL databases will benefit tremendously from the knowledge and techniques this book provides.

Nearly 7,000 new mobile applications appear every day, and a constant stream of data gives them life. Many organizations rely on a predictive analytics model to turn data into useful business information and ensure the predictions remain accurate as data changes. It can be a complex, time-consuming process. This book shows how to automate and accelerate that process using machine learning (ML) on a modern data warehouse that runs on any cloud. Product specialists from MemSQL explain how today’s modern data warehouses provide the foundations to implement ML algorithms that run efficiently. Through several real-time use cases, you’ll learn how to quickly identify the right metrics to make actionable business decisions. This book explores foundational ML and artificial intelligence concepts to help you understand: How data warehouses accelerate deployment and simplify manageability How companies make a choice between cloud and on-premises deployments for building data processing applications Ways to build analytics and visualizations for business intelligence on historical data The technologies and architecture for building and deploying real-time data pipelines This book demonstrates specific models and examples for building supervised and unsupervised real-time ML applications, and gives practical advice on how to make the choice between building an ML pipeline or buying an existing solution. If you need to use data accurately and efficiently, a real-time data warehouse is a critical business tool.

Relational databases haven’t gone away, but they are evolving to integrate messy, disjointed unstructured data into a cleansed repository for analytics. With the execution of massively parallel processing (MPP), the latest generation of analytic data warehouses is helping organizations move beyond business intelligence to processing a variety of advanced analytic workloads. These MPP databases expose their power with the familiarity of SQL. This report introduces the Greenplum Database, recently released as an open source project by Pivotal Software. Lead author Marshall Presser of Pivotal Data Engineering takes you through the Greenplum approach to data analytics and data-driven decisions, beginning with Greenplum’s shared-nothing architecture. You’ll explore data organization and storage, data loading, running queries, as well as performing analytics in the database. You’ll learn: How each networked node in Greenplum’s architecture features an independent operating system, memory, and storage Four deployment options to help you balance security, cost, and time to usability Ways to organize data, including distribution, storage, partitioning, and loading How to use Apache MADlib for in-database analytics, and GPText to process and analyze free-form text Tools for monitoring, managing, securing, and optimizing query responses available in the Pivotal Greenplum commercial database

Book + Content Update Program SQL Server 2016 High Availability Unleashed provides start-to-finish coverage of SQL Server’s powerful high availability (HA) solutions for your traditional on-premise databases, cloud-based databases (Azure or AWS), hybrid databases (on-premise coupled with the cloud), and your emerging Big Data solutions. This complete guide introduces an easy-to-follow, formal HA methodology that has been refined over the past several years and helps you identity the right HA solution for your needs. There is also additional coverage of both disaster recovery and business continuity architectures and considerations. You are provided with step-by-step guides, examples, and sample code to help you set up, manage, and administer these highly available solutions. All examples are based on existing production deployments at major Fortune 500 companies around the globe. This book is for all intermediate-to-advanced SQL Server and Big Data professionals, but is also organized so that the first few chapters are great foundation reading for CIOs, CTOs, and even some tech-savvy CFOs. Learn a formal, high availability methodology for understanding and selecting the right HA solution for your needs Deep dive into Microsoft Cluster Services Use selective data replication topologies Explore thorough details on AlwaysOn and availability groups Learn about HA options with log shipping and database mirroring/ snapshots Get details on Microsoft Azure for Big Data and Azure SQL Explore business continuity and disaster recovery Learn about on-premise, cloud, and hybrid deployments Provide all types of database needs, including online transaction processing, data warehouse and business intelligence, and Big Data Explore the future of HA and disaster recovery In addition, this book is part of InformIT’s exciting Content Update Program, which provides content updates for major technology improvements! As significant updates are made to SQL Server, sections of this book will be updated or new sections will be added to match the updates to the technologies. As updates become available, they will be delivered to you via a free Web Edition of this book, which can be accessed with any Internet connection. To learn more, visit informit.com/cup. How to access the Web Edition: Follow the instructions inside to learn how to register your book to access the FREE Web Edition. * The companion material is not available with the online edition on O'Reilly Learning

Discover the power of SAP Analytics Cloud in solving business intelligence challenges through concise and clear instruction. This book is the essential guide for beginners, providing you a comprehensive understanding of the platform's features and capabilities. By the end, you'll master creating reports, models, and dashboards, making data-driven decisions with confidence. What this Book will help me do Learn how to navigate and utilize the SAP Analytics Cloud interface effectively. Create data models using various sources like Excel or text files for comprehensive insights. Design and compile visually engaging stories, reports, and dashboards effortlessly. Master collaborative and presentation tools inside SAP Digital Boardroom. Understand how to plan, predict, and analyze seamlessly within a single platform. Author(s) None Ahmed is an experienced SAP consultant and analytics professional, bringing years of practical experience in BI tools and enterprise analytics. As an expert in SAP Analytics Cloud, None has guided numerous teams in deploying effective analytics solutions. Their writing aims to demystify complex tools for learners. Who is it for? This book is ideal for IT professionals, business analysts, and newcomers eager to understand SAP Analytics Cloud. Beginner-level BI developers and managers seeking guided steps for mastering this platform will find it invaluable. If you aim to enhance your career in cloud-based analytics, this book is tailored for you.

Abstract Business Intelligence (BI) is a broad term that relates to applications that analyze data to understand and act on the key metrics that drive profitability in an enterprise. Key to analyzing that data is providing fast, easy access to it while delivering it in formats or tools that best fit the needs of the user. At the core of any BI solution are user query and reporting tools that provide intuitive access to data supporting a spectrum of users from executives to “power users,” from spreadsheet aficionados to the external Internet consumer. IBM® DB2® Web Query for i offers a set of modernized tools for a more robust, extensible, and productive reporting solution than the popular IBM Query for System i® tool (also known as IBM Query/400). IBM DB2 Web Query for i preserves investments in the reports that are developed with Query/400 by offering a choice of importing definitions into the new technology or continuing to run existing Query/400 reports as is. But, it also offers significant productivity and performance enhancements by leveraging the latest in DB2 for i query optimization technology. The DB2 Web Query for i product is a web-based query and report writing product that offers enhanced capabilities over the IBM Query for iSeries product (also commonly known as Query/400). IBM DB2 Web Query for i includes Query for iSeries technology to assist customers in their transition to DB2 Web Query. It offers a more modernized, Java based solution for a more robust, extensible, and productive reporting solution. DB2 Web Query provides the ability to query or build reports against data that is stored in DB2 for i (or Microsoft SQL Server) databases through browser-based user interface technologies: Build reports with ease through the web-based, ribbon-like InfoAssist tool that leverages a common look and feel that can extend the number of personnel that can generate their own reports. Simplify the management of reports by significantly reducing the number of report definitions that are required through the use of parameter driven reports. Deliver data to users in many different formats, including directly into spreadsheets, or in boardroom-quality PDF format, or viewed from the browser in HTML. Leverage advanced reporting functions, such as matrix reporting, ranking, color coding, drill-down, and font customization to enhance the visualization of DB2 data. DB2 Web Query offers features to import Query/400 definitions and enhance their look and functions. By using it, you can add OLAP-like slicing and dicing to the reports or view reports in disconnected mode for users on the go. This IBM Redbooks® publication provides a broad understanding of what can be done with the DB2 Web Query product. This publication is a companion of DB2 Web Query Tutorials, SG24-8378, which has a group of self-explanatory tutorials to help you get up to speed quickly.

Prepare for Microsoft Exam 70-768–and help demonstrate your real-world mastery of Business Intelligence (BI) solutions development with SQL Server 2016 Analysis Services (SSAS), including modeling and queries. Designed for experienced IT professionals ready to advance their status, Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the MCSA level. Focus on the expertise measured by these objectives: • Design a multidimensional BI semantic model • Design a tabular BI semantic model • Develop queries using Multidimensional Expressions (MDX) and Data Analysis Expressions (DAX) • Configure and maintain SSAS This Microsoft Exam Ref: • Organizes its coverage by exam objectives • Features strategic, what-if scenarios to challenge you • Assumes you are a database or BI professional with experience creating models, writing MDX or DAX queries, and using SSAS

Leverage the New and Improved Features of Oracle Database 12c Written by Oracle experts Bob Bryla and Robert G. Freeman, this Oracle Press guide describes the myriad new and enhanced capabilities available in the latest Oracle Database release. Inside, you’ll find everything you need to know to get up and running quickly on Oracle Database 12c Release 2. Supported by contributions from Oracle expert Eric Yen, Oracle Database 12c Release 2 New Features offers detailed coverage of: • Installing Oracle Database 12c and Grid Infrastructure • Architectural changes, such as Oracle Multitenant • The most current information on upgrading and migrating to Oracle Database 12c • The pre-upgrade information tool and parallel processing for database upgrades • Oracle Real Application Clusters new features, such as Oracle Flex Cluster, Oracle Flex Automatic Storage Management, and Oracle Automatic Storage Management Cluster File System • Enhanced and new online operations: tables, indexes, and PDBs • Oracle RMAN enhancements, including cross-platform backup and recovery • Oracle Data Guard improvements, such as Fast Sync, and Oracle Active Data Guard new features, such as Far Sync • SQL, PL/SQL, DML, and DDL new features • Improvements to partitioning manageability, performance, and availability • Advanced business intelligence and data warehousing capabilities • Security enhancements, including privileges analysis, data redaction, and new administrative-level privileges • Manageability, performance, and optimization improvements

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.

Optimize reporting and BI with Microsoft SQL Server 2016 Professional Microsoft SQL Server 2016 Reporting Services and Mobile Reports provides a comprehensive lesson in business intelligence (BI), operational reporting and Reporting Services architecture using a clear, concise tutorial approach. You'll learn effective report solution design based upon many years of experience with successful report solutions. Improve your own reports with advanced, best-practice design, usability, query design, and filtering techniques. Expert guidance provides insight into common report types and explains where each could be made more efficient, while providing step-by step instruction on Microsoft SQL Server 2016. All changes to the 2016 release are covered in detail, including improvements to the Visual Studio Report Designer (SQL Server Data Tools) and Report Builder, Mobile Dashboard Designer, the new Report Portal Interface, HTML-5 Rendering, Power BI integration, Custom Parameters Pane, and more. The Microsoft SQL Server 2016 release will include significant changes. New functionality, new capabilities, re-tooled processes, and changing support require a considerable update to existing knowledge. Whether you're starting from scratch or simply upgrading, this book is an essential guide to report design and business intelligence solutions. Understand BI fundamentals and Reporting Services architecture Learn the ingredients to a successful report design Get up to speed on Microsoft SQL Server 2016 Grasp the purpose behind common designs to optimize your reporting Microsoft SQL Server Reporting Services makes reporting faster, easier, and more powerful than ever in web, desktop and portal solutions. Compatibility with an extensive variety of data sources makes it a go-to solution for organizations across the globe. The 2016 release brings some of the biggest changes in years, and the full depth and breadth of these changes can create a serious snag in your workflow. For a clear tutorial geared toward the working professional, Professional Microsoft SQL Server 2016 Reporting Services and Mobile Reports is the ideal guide for getting up to speed and producing successful reports.

With "Tabular Modeling with SQL Server 2016 Analysis Services Cookbook," you'll discover how to harness the full potential of the latest Tabular models in SQL Server Analysis Services (SSAS). This practical guide equips data professionals with the tools, techniques, and knowledge to optimize data analytics and deliver fast, reliable, and impactful business insights. What this Book will help me do Understand the fundamentals of Tabular modeling and its advantages over traditional methods. Use SQL Server 2016 SSAS features to build and deploy Tabular models tailored to business needs. Master DAX for creating powerful calculated fields and optimized measures. Administer and secure your models effectively, ensuring robust BI solutions. Optimize performance and explore advanced features in Tabular solutions for maximum efficiency. Author(s) None Wilson is an experienced SQL BI professional with a strong background in database modeling and analytics. With years of hands-on experience in developing BI solutions, Wilson takes a practical and straightforward teaching approach. Their guidance in this book makes the complex topics of Tabular modeling and SSAS accessible to both seasoned professionals and newcomers to the field. Who is it for? This book is tailored for SQL BI professionals, database architects, and data analysts aiming to leverage Tabular models in SQL Server Analysis Services. It caters to those familiar with database management and basic BI concepts who are eager to improve their analysis solutions. It's a valuable resource if you aim to gain expertise in using tabular modeling for business intelligence.