This book is written in an easytounderstand style, following an enterprise development process through all the phases of development and deployment. Concepts are illustrated with realworld examples and the methods used are explained stepbystep. This book is for Oracle developers looking to start using Oracle’s latest development tool and J2EE developers looking for a more productive way to build modern web applications. This book will guide you through the creation of a successful enterprise application with Oracle ADF 12c, and therefore it assumes you have basic knowledge of Java, JDeveloper, and databases.

Targeted at those with an existing familiarity with R programming, this practical guide will appeal directly to programmers interested in learning effective data visualization techniques with R and a wide-range of its associated libraries.

This book is aimed at both new developers as well as experienced developers. If you are a new SAP BusinessObjects Universe developer who is looking for a step-by-step guide supported with real-life examples and illustrated diagrams, then this book is for you. If you are a seasoned BusinessObjects Universe developer who is looking for a fast way to map your old experience in Universe designer to the newer Information Design Tool, then this book is for you as well.

If you are a Visual Studio 2013 or .NET developer who would like to sharpen your existing skill set and adapt to new .NET technologies, this is the book for you. A basic understanding of .NET and C# is required.

This book provides an overview of the kill chain approach to penetration testing, and then focuses on using Kali Linux to provide examples of how this methodology is applied in the real world. After describing the underlying concepts, step-by-step examples are provided that use selected tools to demonstrate the techniques.If you are an IT professional or a security consultant who wants to maximize the success of your network testing using some of the advanced features of Kali Linux, then this book is for you. This book will teach you how to become an expert in the pre-engagement, management, and documentation of penetration testing by building on your understanding of Kali Linux and wireless concepts.

This book is intended for middleware system administrators and Java developers, actually good Java developers, who care about architecture design and implementation. Whether you are new to WildFly, come from a previous version, such as JBoss AS 5, 6, and 7, or are an expert in it, you will be able to master both the basic and advanced features of WildFly. By the way, most of the core components of WildFly are totally new, such as its administration tool, that is, the CLI; its operational modes, which are, the standalone and domain modes; and its web server provided by Undertow, you can benefit from this book even if you have no experience in JBoss and WildFly at all.

You will be led carefully stepbystep through a detailed set of recipes. This book focuses on web content management using Microsoft SharePoint 2013 server. The practical examples are built logically throughout the chapters to create a common theme. This book is ideal for developers who want to broaden their understanding of the web content management features available with SharePoint 2013. It is assumed that you already have some experience using SharePoint and developing web content. Experience with Microsoft PowerShell and coding C# with Visual Studio will also be helpful, but is not essential.

Written in a stepbystep, tutorial style with a lot of code snippets and handson examples to create an advanced Magento theme from scratch, this book is tailormade for web designers and developers. This book is great for developers and web designers who are looking to get a good grounding in how to create custom, responsive, and advanced Magento themes. Readers must have some experience with HTML, PHP, CSS, and Magento theme design. This book will be useful for anybody who already has knowledge of the Magento frontend structure.

This book focuses on readers starting their journey with Hyper-V, and assumes they have minimal or no knowledge of virtualization.

Step-by-step recipes filled with practical code samples and engaging examples demonstrate Haskell in practice, and then the concepts behind the code. This book shows functional developers and analysts how to leverage their existing knowledge of Haskell specifically for high-quality data analysis. A good understanding of data sets and functional programming is assumed.

Master machine learning techniques with R to deliver insights for complex projectsAbout This BookGet to grips with the application of Machine Learning methods using an extensive set of R packagesUnderstand the benefits and potential pitfalls of using machine learning methodsImplement the numerous powerful features offered by R with this comprehensive guide to building an independent R-based ML system Who This Book Is For If you want to learn how to use R's machine learning capabilities to solve complex business problems, then this book is for you. Some experience with R and a working knowledge of basic statistical or machine learning will prove helpful.What You Will LearnGain deep insights to learn the applications of machine learning tools to the industryManipulate data in R efficiently to prepare it for analysisMaster the skill of recognizing techniques for effective visualization of dataUnderstand why and how to create test and training data sets for analysisFamiliarize yourself with fundamental learning methods such as linear and logistic regressionComprehend advanced learning methods such as support vector machinesRealize why and how to apply unsupervised learning methods In Detail Machine learning is a field of Artificial Intelligence to build systems that learn from data. Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning to your data. The book starts with introduction to Cross-Industry Standard Process for Data Mining. It takes you through Multivariate Regression in detail. Moving on, you will also address Classification and Regression trees. You will learn a couple of “Unsupervised techniques”. Finally, the book will walk you through text analysis and time series. The book will deliver practical and real-world solutions to problems and variety of tasks such as complex recommendation systems. By the end of this book, you will gain expertise in performing R machine learning and will be able to build complex ML projects using R and its packages.Style and approach This is a book explains complicated concepts with easy to follow theory and real-world, practical applications. It demonstrates the power of R and machine learning extensively while highlighting the constraints.

Generate effective results in a variety of visually appealing charts using the plotting packages in PythonAbout This BookExplore various tools and their strengths while building meaningful representations that can make it easier to understand dataPacked with computational methods and algorithms in diverse fields of scienceWritten in an easy-to-follow categorical style, this book discusses some niche techniques that will make your code easier to work with and reuse Who This Book Is For If you are a Python developer who performs data visualization and wants to develop existing knowledge about Python to build analytical results and produce some amazing visual display, then this book is for you. A basic knowledge level and understanding of Python libraries is assumed.What You Will LearnGather, cleanse, access, and map data to a visual frameworkRecognize which visualization method is applicable and learn best practices for data visualizationGet acquainted with reader-driven narratives and author-driven narratives and the principles of perceptionUnderstand why Python is an effective tool to be used for numerical computation much like MATLAB, and explore some interesting data structures that come with itExplore with various visualization choices how Python can be very useful in computation in the field of finance and statisticsGet to know why Python is the second choice after Java, and is used frequently in the field of machine learningCompare Python with other visualization approaches using Julia and a JavaScript-based framework such as D3.jsDiscover how Python can be used in conjunction with NoSQL such as Hive to produce results efficiently in a distributed environment In Detail Python has a handful of open source libraries for numerical computations involving optimization, linear algebra, integration, interpolation, and other special functions using array objects, machine learning, data mining, and plotting. Pandas have a productive environment for data analysis. These libraries have a specific purpose and play an important role in the research into diverse domains including economics, finance, biological sciences, social science, health care, and many more. The variety of tools and approaches available within Python community is stunning, and can bolster and enhance visual story experiences. This book offers practical guidance to help you on the journey to effective data visualization. Commencing with a chapter on the data framework, which explains the transformation of data into information and eventually knowledge, this book subsequently covers the complete visualization process using the most popular Python libraries with working examples. You will learn the usage of Numpy, Scipy, IPython, MatPlotLib, Pandas, Patsy, and Scikit-Learn with a focus on generating results that can be visualized in many different ways. Further chapters are aimed at not only showing advanced techniques such as interactive plotting; numerical, graphical linear, and non-linear regression; clustering and classification, but also in helping you understand the aesthetics and best practices of data visualization. The book concludes with interesting examples such as social networks, directed graph examples in real-life, data structures appropriate for these problems, and network analysis. By the end of this book, you will be able to effectively solve a broad set of data analysis problems.Style and approach The approach of this book is not step by step, but rather categorical. The categories are based on fields such as bioinformatics, statistical and machine learning, financial computation, and linear algebra. This approach is beneficial for the community in many different fields of work and also helps you learn how one approach can make sense across many fields

Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization About This Book Handle your data with precision and care for optimal business intelligence Restructure and transform your data to inform decision-making Packed with practical advice and tips to help you get to grips with data mining Who This Book Is For If you are a data scientist or R developer who wants to explore and optimize your use of R’s advanced features and tools, this is the book for you. A basic knowledge of R is required, along with an understanding of database logic. What You Will Learn Connect to and load data from R’s range of powerful databases Successfully fetch and parse structured and unstructured data Transform and restructure your data with efficient R packages Define and build complex statistical models with glm Develop and train machine learning algorithms Visualize social networks and graph data Deploy supervised and unsupervised classification algorithms Discover how to visualize spatial data with R In Detail R is an essential language for sharp and successful data analysis. Its numerous features and ease of use make it a powerful way of mining, managing, and interpreting large sets of data. In a world where understanding big data has become key, by mastering R you will be able to deal with your data effectively and efficiently. This book will give you the guidance you need to build and develop your knowledge and expertise. Bridging the gap between theory and practice, this book will help you to understand and use data for a competitive advantage. Beginning with taking you through essential data mining and management tasks such as munging, fetching, cleaning, and restructuring, the book then explores different model designs and the core components of effective analysis. You will then discover how to optimize your use of machine learning algorithms for classification and recommendation systems beside the traditional and more recent statistical methods. Style and approach Covering the essential tasks and skills within data science, Mastering Data Analysis provides you with solutions to the challenges of data science. Each section gives you a theoretical overview before demonstrating how to put the theory to work with real-world use cases and hands-on examples.

"Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python. About This Book ?Explore and create intelligent systems using cutting-edge deep learning techniques ?Implement deep learning algorithms and work with revolutionary libraries in Python ?Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and more Who This Book Is For This book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired. What You Will Learn ?Get a practical deep dive into deep learning algorithms ?Explore deep learning further with Theano, Caffe, Keras, and TensorFlow ?Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders and Restricted Boltzmann Machines ?Dive into Deep Belief Nets and Deep Neural Networks ?Discover more deep learning algorithms with Dropout and Convolutional Neural Networks ?Get to know device strategies so you can use deep learning algorithms and libraries in the real world In Detail With an increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries. The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results. Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques. Whether you want to dive deeper into Deep Learning, or want to investigate how to get more out of this powerful technology, you'll find everything inside. Style and approach Python Machine Learning by example follows practical hands on approach. It walks you through the key elements of Python and its powerful machine learning libraries with the help of real world projects. "

Creating and Sharing Maps and Data using ArcGIS Pro About This Book ? Leverage the power of ArcGIS to build beautiful 2D and 3D maps. ? Work with ArcGIS to analyze and process data. ? Extend the power of ArcGIS to ArcGIS Online to create and edit content. Who This Book Is For GIS developers who are comfortable using ArcGIS, and are looking to increase their capabilities and skills, will find this book useful. What You Will Learn ? Edit data using standard tools and topology ? Convert and link data together using joins and relates ? Create and share data using Projections and Coordinate Systems ? Access and collect data in the field using ArcGIS Collector ? Perform proximity analysis and map clusters with hotspot analysis ? Use the 3D Analyst Extension and perform advanced 3D analysis ? Share maps and data using ArcGIS Online via web and mobile apps In Detail ArcGIS is Esri's catalog of GIS applications with powerful tools for visualizing, maintaining, and analyzing data. ArcGIS makes use of the modern ribbon interface and 64-bit processing to increase the speed and efficiency of using GIS. It allows users to create amazing maps in both 2D and 3D quickly and easily. If you want to gain a thorough understanding of the various data formats that can be used in ArcGIS Pro and shared via ArcGIS Online, then this book is for you. Beginning with a refresher on ArcGIS Pro and how to work with projects, this book will quickly take you through recipes about using various data formats supported by the tool. You will learn the limits of each format, such as Shapefiles, Geodatabase, and CAD files, and learn how to link tables from outside sources to existing GIS data to expand the amount of data that can be used in ArcGIS. You'll learn methods for editing 2D and 3D data using ArcGIS Pro and how topology can be used to ensure data integrity. Lastly the book will show you how data and maps can be shared via ArcGIS Online and used with web and mobile applications. Style and approach This book takes a recipe-based approach, teaching you how to create and share maps and data using ArcGIS Pro.

Incorporate the power of Einstein in your Salesforce application About This Book ? Make better predictions of your business processes using prediction and predictive modeling ? Build your own custom models by leveraging PredictionIO on the Heroku platform ? Integrate Einstein into various cloud services to predict sales, marketing leads, insights into news feeds, and more Who This Book Is For This book is for developers, data scientists, and Salesforce-experienced consultants who want to explore Salesforce Einstein and its current offerings. It assumes some prior experience with the Salesforce platform. What You Will Learn ? Get introduced to AI and its role in CRM and cloud applications ? Understand how Einstein works for the sales, service, marketing, community, and commerce clouds ? Gain a deep understanding of how to use Einstein for the analytics cloud ? Build predictive apps on Heroku using PredictionIO, and work with Einstein Predictive Vision Services ? Incorporate Einstein in the IoT cloud ? Test the accuracy of Einstein through Salesforce reporting and Wave analytics In Detail Dreamforce 16 brought forth the latest addition to the Salesforce platform: an AI tool named Einstein. Einstein promises to provide users of all Salesforce applications with a powerful platform to help them gain deep insights into the data they work on. This book will introduce you to Einstein and help you integrate it into your respective business applications based on the Salesforce platform. We start off with an introduction to AI, then move on to look at how AI can make your CRM and apps smarter. Next, we discuss various out-of-the-box components added to sales, service, marketing, and community clouds from salesforce to add Artificial Intelligence capabilities. Further on, we teach you how to use Heroku, PredictionIO, and the force.com platform, along with Einstein, to build smarter apps. The core chapters focus on developer content and introduce PredictionIO and Salesforce Einstein Vision Services. We explore Einstein Predictive Vision Services, along with analytics cloud, the Einstein Data Discovery product, and IOT core concepts. Throughout the book, we also focus on how Einstein can be integrated into CRM and various clouds such as sales, services, marketing, and communities. By the end of the book, you will be able to embrace and leverage the power of Einstein, incorporating its functions to gain more knowledge. Salesforce developers will be introduced to the world of AI, while data scientists will gain insights into Salesforce’s various cloud offerings and how they can use Einstein’s capabilities and enhance applications. Style and approach This book takes a straightforward approach to explain Salesforce Einstein and all of its potential applications. Filled with examples, the book presents the facts along with seasoned advice and real-world use cases to ensure you have all the resources you need to incorporate the power of Einstein in your work.

More than 80 recipes to help you leverage the various extensibility features available for Microsoft Dynamics and solve problems easily About This Book ? Customize, configure, and extend the vanilla features of Dynamics 365 to deliver bespoke CRM solutions fit for any organization ? Implement business logic using point-and-click configuration, plugins, and client-side *s with MS Dynamics 365 ? Built a DevOps pipeline as well as Integrate Dynamics 365 with Azure and other platforms Who This Book Is For This book is for developers, administrators, consultants, and power users who want to learn about best practices when extending Dynamics 365 for enterprises. You are expected to have a basic understand of the Dynamics CRM/365 platform. What You Will Learn ? Customize, configure, and extend Microsoft Dynamics 365 ? Create business process automation ? Develop client-side extensions to add features to the Dynamics 365 user interface ? Set up a security model to securely manage data with Dynamics 365 ? Develop and deploy clean code plugins to implement a wide range of custom behaviors ? Use third-party applications, tools, and patterns to integrate Dynamics 365 with other platforms ? Integrate with Azure, Java, SSIS, PowerBI, and Octopus Deploy ? Build an end-to-end DevOps pipeline for Dynamics 365 In Detail Microsoft Dynamics 365 is a powerful tool. It has many unique features that empower organisations to bridge common business challenges and technology pitfalls that would usually hinder the adoption of a CRM solution. This book sets out to enable you to harness the power of Dynamics 365 and cater to your unique circumstances. We start this book with a no-code configuration chapter and explain the schema, fields, and forms modeling techniques. We then move on to server-side and client-side custom code extensions. Next, you will see how best to integrate Dynamics 365 in a DevOps pipeline to package and deploy your extensions to the various SDLC environments. This book also covers modern libraries and integration patterns that can be used with Dynamics 365 (Angular, 3 tiers, and many others). Finally, we end by highlighting some of the powerful extensions available. Throughout we explain a range of design patterns and techniques that can be used to enhance your code quality; the aim is that you will learn to write enterprise-scale quality code. Style and approach This book takes a recipe-based approach, delivering practical examples and use cases so that you can identify the best possible approach to extend your Dynamics 365 deployment and tackle your specific business problems.

Design, implement, and deliver successful streaming applications, machine learning pipelines and graph applications using Spark SQL API About This Book ? Learn about the design and implementation of streaming applications, machine learning pipelines, deep learning, and large-scale graph processing applications using Spark SQL APIs and Scala. ? Learn data exploration, data munging, and how to process structured and semi-structured data using real-world datasets and gain hands-on exposure to the issues and challenges of working with noisy and "dirty" real-world data. ? Understand design considerations for scalability and performance in web-scale Spark application architectures. Who This Book Is For If you are a developer, engineer, or an architect and want to learn how to use Apache Spark in a web-scale project, then this is the book for you. It is assumed that you have prior knowledge of SQL querying. A basic programming knowledge with Scala, Java, R, or Python is all you need to get started with this book. What You Will Learn ? Familiarize yourself with Spark SQL programming, including working with DataFrame/Dataset API and SQL ? Perform a series of hands-on exercises with different types of data sources, including CSV, JSON, Avro, MySQL, and MongoDB ? Perform data quality checks, data visualization, and basic statistical analysis tasks ? Perform data munging tasks on publically available datasets ? Learn how to use Spark SQL and Apache Kafka to build streaming applications ? Learn key performance-tuning tips and tricks in Spark SQL applications ? Learn key architectural components and patterns in large-scale Spark SQL applications In Detail In the past year, Apache Spark has been increasingly adopted for the development of distributed applications. Spark SQL APIs provide an optimized interface that helps developers build such applications quickly and easily. However, designing web-scale production applications using Spark SQL APIs can be a complex task. Hence, understanding the design and implementation best practices before you start your project will help you avoid these problems. This book gives an insight into the engineering practices used to design and build real-world, Spark-based applications. The book's hands-on examples will give you the required confidence to work on any future projects you encounter in Spark SQL. It starts by familiarizing you with data exploration and data munging tasks using Spark SQL and Scala. Extensive code examples will help you understand the methods used to implement typical use-cases for various types of applications. You will get a walkthrough of the key concepts and terms that are common to streaming, machine learning, and graph applications. You will also learn key performance-tuning details including Cost Based Optimization (Spark 2.2) in Spark SQL applications. Finally, you will move on to learning how such systems are architected and deployed for a successful delivery of your project. Style and approach This book is a hands-on guide to designing, building, and deploying Spark SQL-centric production applications at scale.

Secure your Oracle Database 12c with this valuable Oracle support resource, featuring more than 100 solutions to the challenges of protecting your data About This Book Explore and learn the new security features introduced in Oracle Database 12c, to successfully secure your sensitive data Learn how to identify which security strategy is right for your needs – and how to apply it Each ‘recipe’ provides you with a single step-by-step solution, making this book a vital resource, delivering Oracle support in one accessible place Who This Book Is For This book is for DBAs, developers, and architects who are keen to know more about security in Oracle Database 12c. This book is best suited for beginners and intermediate-level database security practitioners. Basic knowledge of Oracle Database is expected, but no prior experience of securing a database is required. What You Will Learn Analyze application privileges and reduce the attack surface Reduce the risk of data exposure by using Oracle Data Redaction and Virtual Private Database Control data access and integrity in your organization using the appropriate database feature or option Learn how to protect your databases against application bypasses Audit user activity using the new auditing architecture Restrict highly privileged users from accessing data Encrypt data in Oracle Database Work in a real-world environment where a multi-layer security strategy is applied In Detail Businesses around the world are paying much greater attention toward database security than they ever have before. Not only does the current regulatory environment require tight security, particularly when dealing with sensitive and personal data, data is also arguably a company’s most valuable asset - why wouldn’t you want to protect it in a secure and reliable databaseOracle Database lets you do exactly that. It’s why it is one of the world’s leading databases – with a rich portfolio of features to protect data from contemporary vulnerabilities, it’s the go-to database for many organizations. Oracle Database 12c Security Cookbook helps DBAs, developers, and architects to better understand database security challenges. Let it guide you through the process of implementing appropriate security mechanisms, helping you to ensure you are taking proactive steps to keep your data safe. Featuring solutions for common security problems in the new Oracle Database 12c, with this book you can be confident about securing your database from a range of different threats and problems. Style and approach Each chapter explains the different aspects of security through a series of recipes. Each recipe presents instructions in a step-by-step manner, supported by explanations of the topic.

Over 170 advanced recipes to search, analyze, deploy, manage, and monitor data effectively with Elasticsearch 5.x About This Book Deploy and manage simple Elasticsearch nodes as well as complex cluster topologies Write native plugins to extend the functionalities of Elasticsearch 5.x to boost your business Packed with clear, step-by-step recipes to walk you through the capabilities of Elasticsearch 5.x Who This Book Is For If you are a developer who wants to get the most out of Elasticsearch for advanced search and analytics, this is the book for you. Some understanding of JSON is expected. If you want to extend Elasticsearch, understanding of Java and related technologies is also required. What You Will Learn Choose the best Elasticsearch cloud topology to deploy and power it up with external plugins Develop tailored mapping to take full control of index steps Build complex queries through managing indices and documents Optimize search results through executing analytics aggregations Monitor the performance of the cluster and nodes Install Kibana to monitor cluster and extend Kibana for plugins Integrate Elasticsearch in Java, Scala, Python and Big Data applications In Detail Elasticsearch is a Lucene-based distributed search server that allows users to index and search unstructured content with petabytes of data. This book is your one-stop guide to master the complete Elasticsearch ecosystem. We’ll guide you through comprehensive recipes on what’s new in Elasticsearch 5.x, showing you how to create complex queries and analytics, and perform index mapping, aggregation, and *ing. Further on, you will explore the modules of Cluster and Node monitoring and see ways to back up and restore a snapshot of an index. You will understand how to install Kibana to monitor a cluster and also to extend Kibana for plugins. Finally, you will also see how you can integrate your Java, Scala, Python, and Big Data applications such as Apache Spark and Pig with Elasticsearch, and add enhanced functionalities with custom plugins. By the end of this book, you will have an in-depth knowledge of the implementation of the Elasticsearch architecture and will be able to manage data efficiently and effectively with Elasticsearch. Style and approach This book follows a problem-solution approach to effectively use and manage Elasticsearch. Each recipe focuses on a particular task at hand, and is explained in a very simple, easy to understand manner.

Over 70 practical recipes to analyze multi-dimensional data in SQL Server 2016 Analysis Services cubes About This Book Updated for SQL Server 2016, this book helps you take advantage of the new MDX commands and the new features introduced in SSAS Perform time-related, context-aware, and business related-calculations with ease to enrich your Business Intelligence solutions Collection of techniques to write flexible and high performing MDX queries in SSAS with carefully structured examples Who This Book Is For This book is for anyone who has been involved in working with multidimensional data. If you are a multidimensional cube developer, a multidimensional database administrator, or a report developer who writes MDX queries to access multidimensional cube, this book will help you. If you are a power cube user or an experienced business analyst, you will also find this book invaluable in your data analysis. This book is for you are interested in doing more data analysis so that the management can make timely and accurate business decisions. What You Will Learn Grasp the fundamental MDX concepts, features, and techniques Work with sets Work with Time dimension and create time-aware calculations Make analytical reports compact, concise, and efficient Navigate cubes Master MDX for reporting with Reporting Services (new) Perform business analytics Design efficient cubes and efficient MDX queries Create metadata-driven calculations (new) Capture MDX queries and many other techniques In Detail If you're often faced with MDX challenges, this is a book for you. It will teach you how to solve various real-world business requirements using MDX queries and calculations. Examples in the book introduce an idea or a problem and then guide you through the process of implementing the solution in a step-by-step manner, inform you about the best practices and offer a deep knowledge in terms of how the solution works. Recipes are organized by chapters, each covering a single topic. They start slowly and logically progress to more advanced techniques. In case of complexity, things are broken down. Instead of one, there are series of recipes built one on top of another. This way you are able to see intermediate results and debug potential errors faster. Finally, the cookbook format is here to help you quickly identify the topic of interest and in it a wide range of practical solutions, that is – MDX recipes for your success. Style and approach This book is written in a cookbook format, where you can browse through and look for solutions to a particular problem in one place. Each recipe is short, to the point and grouped by relevancy. All the recipes are sequenced in a logical progression; you will be able to build up your understanding of the topic incrementally.