Migrating your application to a cloud-based serverless architecture doesn't have to be difficult. Reduce complexity and minimize the time you spend administering servers or worrying about availability with this comprehensive guide to serverless applications on Azure. Key Features Provides information on integration of Azure products Plan and implement your own serverless backend to meet tried-and-true development standards Includes step-by-step instructions to help you navigate advanced concepts and application integrations Book DescriptionMany businesses are rapidly adopting a microservices-first approach to development, driven by the availability of new commercial services like Azure Functions and AWS Lambda. In this book, we'll show you how to quickly get up and running with your own serverless development on Microsoft Azure. We start by working through a single function, and work towards integration with other Azure services like App Insights and Cosmos DB to handle common user requirements like analytics and highly performant distributed storage. We finish up by providing you with the context you need to get started on a larger project of your own choosing, leaving you equipped with everything you need to migrate to a cloud-first serverless solution. What you will learn Identify the key advantages and disadvantages of serverless development Build a fully-functioning serverless application and utilize a wide variety of Azure services Create, deploy, and manage your own Azure Functions in the cloud Implement core design principles for writing effective serverless code Who this book is forThis book is ideal for back-end developers or engineers who want a quick hands-on introduction to developing serverless applications within the Microsoft ecosystem.

The final edition of the incomparable data warehousing and business intelligence reference, updated and expanded The Kimball Group Reader, Remastered Collection is the essential reference for data warehouse and business intelligence design, packed with best practices, design tips, and valuable insight from industry pioneer Ralph Kimball and the Kimball Group. This Remastered Collection represents decades of expert advice and mentoring in data warehousing and business intelligence, and is the final work to be published by the Kimball Group. Organized for quick navigation and easy reference, this book contains nearly 20 years of experience on more than 300 topics, all fully up-to-date and expanded with 65 new articles. The discussion covers the complete data warehouse/business intelligence lifecycle, including project planning, requirements gathering, system architecture, dimensional modeling, ETL, and business intelligence analytics, with each group of articles prefaced by original commentaries explaining their role in the overall Kimball Group methodology. Data warehousing/business intelligence industry's current multi-billion dollar value is due in no small part to the contributions of Ralph Kimball and the Kimball Group. Their publications are the standards on which the industry is built, and nearly all data warehouse hardware and software vendors have adopted their methods in one form or another. This book is a compendium of Kimball Group expertise, and an essential reference for anyone in the field. * Learn data warehousing and business intelligence from the field's pioneers * Get up to date on best practices and essential design tips * Gain valuable knowledge on every stage of the project lifecycle * Dig into the Kimball Group methodology with hands-on guidance Ralph Kimball and the Kimball Group have continued to refine their methods and techniques based on thousands of hours of consulting and training. This Remastered Collection of The Kimball Group Reader represents their final body of knowledge, and is nothing less than a vital reference for anyone involved in the field.

Leverage the power of Redis 4.x to develop, optimize and administer your Redis solutions with ease Key Features Build, deploy and administer high performance and scalable applications in Redis Covers a range of important tasks - including development and administration of Redis A practical guide that takes your understanding of Redis to the next level Book DescriptionRedis is considered the world's most popular key-value store database. Its versatility and the wide variety of use cases it enables have made it a popular choice of database for many enterprises. Based on the latest version of Redis, this book provides both step-by-step recipes and relevant the background information required to utilize its features to the fullest. It covers everything from a basic understanding of Redis data types to advanced aspects of Redis high availability, clustering, administration, and troubleshooting. This book will be your great companion to master all aspects of Redis. The book starts off by installing and configuring Redis for you to get started with ease. Moving on, all the data types and features of Redis are introduced in detail. Next, you will learn how to develop applications with Redis in Java, Python, and the Spring Boot web framework. You will also learn replication tasks, which will help you to troubleshoot replication issues. Furthermore, you will learn the steps that need to be undertaken to ensure high availability on your cluster and during production deployment. Toward the end of the book, you will learn the topmost tasks that will help you to troubleshoot your ecosystem efficiently, along with extending Redis by using different modules. What you will learn Install and configure your Redis instance Explore various data types and commands in Redis Build client-side applications as well as a Big Data framework with Redis Manage data replication and persistence in Redis Implement high availability and data sharding in Redis Extend Redis with Redis Module Benchmark, debug, fine-tune and troubleshoot various issues in Redis Who this book is forThis book is for database administrators, developers and architects who want to tackle the common and not so common problems associated with the different development and administration-related tasks in Redis. A fundamental understanding of Redis is expected to get the best out of this book.

Unleash the power of serverless integration with Azure About This Book * Build and support highly available and scalable API Apps by learning powerful Azure-based cloud integration * Deploy and deliver applications that integrate seamlessly in the cloud and quickly adapt as per your integration needs * Deploy hybrid applications that work and integrate on the cloud (using Logic Apps and BizTalk Server) Who This Book Is For This book is for Microsoft Enterprise developers, DevOps, and IT professionals who would like to use Azure App Service and Microsoft Cloud Integration technologies to create cloud-based web and mobile apps. What You Will Learn * Explore new models of robust cloud integration in Microsoft Azure * Create your own connector and learn how to publish and manage it * Build reliable, scalable, and secure business workflows using Azure Logic Apps * Simplify SaaS connectivity with Azure using Logic Apps * Connect your on-premises system to Azure securely * Get to know more about Logic Apps and how to connect to on-premises "line-of-business" applications using Microsoft BizTalk Server In Detail Microsoft is focusing heavily on Enterprise connectivity so that developers can build scalable web and mobile apps and services in the cloud. In short, Enterprise connectivity from anywhere and to any device. These integration services are being offered through powerful Azure-based services. This book will teach you how to design and implement cloud integration using Microsoft Azure. It starts by showing you how to build, deploy, and secure the API app. Next, it introduces you to Logic Apps and helps you quickly start building your integration applications. We'll then go through the different connectors available for Logic Apps to build your automated business process workflow. Further on, you will see how to create a complex workflow in Logic Apps using Azure Function. You will then add a SaaS application to your existing cloud applications and create Queues and Topics in Service Bus on Azure using Azure Portal. Towards the end, we'll explore event hubs and IoT hubs, and you'll get to know more about how to tool and monitor the business workflow in Logic Apps. Using this book, you will be able to support your apps that connect to data anywhere-be it in the cloud or on-premises. Style and approach This practical hands-on tutorial shows you the full capability of App Service and other Azure-based integration services to build scalable and highly available web and mobile apps. It helps you successfully build and support your applications in the cloud or on-premises successfully. We'll debunk the popular myth that switching to cloud is risky-it's not!

Master the intricacies of Elasticsearch 5 and use it to create flexible and scalable search solutions About This Book * Master the searching, indexing, and aggregation features in ElasticSearch * Improve users' search experience with Elasticsearch's functionalities and develop your own Elasticsearch plugins * A comprehensive, step-by-step guide to master the intricacies of ElasticSearch with ease Who This Book Is For If you have some prior working experience with Elasticsearch and want to take your knowledge to the next level, this book will be the perfect resource for you.If you are a developer who wants to implement scalable search solutions with Elasticsearch, this book will also help you. Some basic knowledge of the query DSL and data indexing is required to make the best use of this book. What You Will Learn * Understand Apache Lucene and Elasticsearch 5's design and architecture * Use and configure the new and improved default text scoring mechanism in Apache Lucene 6 * Know how to overcome the pitfalls while handling relational data in Elasticsearch * Learn about choosing the right queries according to the use cases and master the scripting module including new default scripting language, painlessly * Explore the right way of scaling production clusters to improve the performance of Elasticsearch * Master the searching, indexing, and aggregation features in Elasticsearch * Develop your own Elasticsearch plugins to extend the functionalities of Elasticsearch In Detail Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. Elasticsearch leverages the capabilities of Apache Lucene, and provides a new level of control over how you can index and search even huge sets of data. This book will give you a brief recap of the basics and also introduce you to the new features of Elasticsearch 5. We will guide you through the intermediate and advanced functionalities of Elasticsearch, such as querying, indexing, searching, and modifying data. We'll also explore advanced concepts, including aggregation, index control, sharding, replication, and clustering. We'll show you the modules of monitoring and administration available in Elasticsearch, and will also cover backup and recovery. You will get an understanding of how you can scale your Elasticsearch cluster to contextualize it and improve its performance. We'll also show you how you can create your own analysis plugin in Elasticsearch. By the end of the book, you will have all the knowledge necessary to master Elasticsearch and put it to efficient use. Style and approach This comprehensive guide covers intermediate and advanced concepts in Elasticsearch as well as their implementation. An easy-to-follow approach means you'll be able to master even advanced querying, searching, and administration tasks with ease.

Data Storage: Systems, Management and Security Issues begins with a chapter comparing digital or electronic storage systems, such as magnetic, optical, and flash, with biological data storage systems, like DNA and human brain memory. In the main part of the chapter, the following quantitative storage traits are discussed: data organisation, functionality, data density, capacity, power consumption, redundancy, integrity, access time, data transfer rate. Afterwards, various facets of data warehouses as well as the necessity for security measures are reviewed. Because the significance of security tools is greater than ever before, the pertinent strategies and economics are discussed. The final chapter supplements this by discussing media and storage systems reliability and confidentiality in order to make a greater claim about storage security. Confidentiality, integrity and availability are three aspects of security identified as ones that should be preserved during data transmission, processing and storage.

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.

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.

Harness the power of SQL Server 2017 Integration Services to build your data integration solutions with ease About This Book * Acquaint yourself with all the newly introduced features in SQL Server 2017 Integration Services * Program and extend your packages to enhance their functionality * This detailed, step-by-step guide covers everything you need to develop efficient data integration and data transformation solutions for your organization Who This Book Is For This book is ideal for software engineers, DW/ETL architects, and ETL developers who need to create a new, or enhance an existing, ETL implementation with SQL Server 2017 Integration Services. This book would also be good for individuals who develop ETL solutions that use SSIS and are keen to learn the new features and capabilities in SSIS 2017. What You Will Learn * Understand the key components of an ETL solution using SQL Server 2016-2017 Integration Services * Design the architecture of a modern ETL solution * Have a good knowledge of the new capabilities and features added to Integration Services * Implement ETL solutions using Integration Services for both on-premises and Azure data * Improve the performance and scalability of an ETL solution * Enhance the ETL solution using a custom framework * Be able to work on the ETL solution with many other developers and have common design paradigms or techniques * Effectively use scripting to solve complex data issues In Detail SQL Server Integration Services is a tool that facilitates data extraction, consolidation, and loading options (ETL), SQL Server coding enhancements, data warehousing, and customizations. With the help of the recipes in this book, you'll gain complete hands-on experience of SSIS 2017 as well as the 2016 new features, design and development improvements including SCD, Tuning, and Customizations. At the start, you'll learn to install and set up SSIS as well other SQL Server resources to make optimal use of this Business Intelligence tools. We'll begin by taking you through the new features in SSIS 2016/2017 and implementing the necessary features to get a modern scalable ETL solution that fits the modern data warehouse. Through the course of chapters, you will learn how to design and build SSIS data warehouses packages using SQL Server Data Tools. Additionally, you'll learn to develop SSIS packages designed to maintain a data warehouse using the Data Flow and other control flow tasks. You'll also be demonstrated many recipes on cleansing data and how to get the end result after applying different transformations. Some real-world scenarios that you might face are also covered and how to handle various issues that you might face when designing your packages. At the end of this book, you'll get to know all the key concepts to perform data integration and transformation. You'll have explored on-premises Big Data integration processes to create a classic data warehouse, and will know how to extend the toolbox with custom tasks and transforms. Style and approach This cookbook follows a problem-solution approach and tackles all kinds of data integration scenarios by using the capabilities of SQL Server 2016 Integration Services. This book is well supplemented with screenshots, tips, and tricks. Each recipe focuses on a particular task and is written in a very easy-to-follow manner.

A handy reference guide for data analysts and data scientists to help to obtain value from big data analytics using Spark on Hadoop clusters About This Book * This book is based on the latest 2.0 version of Apache Spark and 2.7 version of Hadoop integrated with most commonly used tools. * Learn all Spark stack components including latest topics such as DataFrames, DataSets, GraphFrames, Structured Streaming, DataFrame based ML Pipelines and SparkR. * Integrations with frameworks such as HDFS, YARN and tools such as Jupyter, Zeppelin, NiFi, Mahout, HBase Spark Connector, GraphFrames, H2O and Hivemall. Who This Book Is For Though this book is primarily aimed at data analysts and data scientists, it will also help architects, programmers, and practitioners. Knowledge of either Spark or Hadoop would be beneficial. It is assumed that you have basic programming background in Scala, Python, SQL, or R programming with basic Linux experience. Working experience within big data environments is not mandatory. What You Will Learn * Find out and implement the tools and techniques of big data analytics using Spark on Hadoop clusters with wide variety of tools used with Spark and Hadoop * Understand all the Hadoop and Spark ecosystem components * Get to know all the Spark components: Spark Core, Spark SQL, DataFrames, DataSets, Conventional and Structured Streaming, MLLib, ML Pipelines and Graphx * See batch and real-time data analytics using Spark Core, Spark SQL, and Conventional and Structured Streaming * Get to grips with data science and machine learning using MLLib, ML Pipelines, H2O, Hivemall, Graphx, SparkR and Hivemall. In Detail Big Data Analytics book aims at providing the fundamentals of Apache Spark and Hadoop. All Spark components - Spark Core, Spark SQL, DataFrames, Data sets, Conventional Streaming, Structured Streaming, MLlib, Graphx and Hadoop core components - HDFS, MapReduce and Yarn are explored in greater depth with implementation examples on Spark + Hadoop clusters. It is moving away from MapReduce to Spark. So, advantages of Spark over MapReduce are explained at great depth to reap benefits of in-memory speeds. DataFrames API, Data Sources API and new Data set API are explained for building Big Data analytical applications. Real-time data analytics using Spark Streaming with Apache Kafka and HBase is covered to help building streaming applications. New Structured streaming concept is explained with an IOT (Internet of Things) use case. Machine learning techniques are covered using MLLib, ML Pipelines and SparkR and Graph Analytics are covered with GraphX and GraphFrames components of Spark. Readers will also get an opportunity to get started with web based notebooks such as Jupyter, Apache Zeppelin and data flow tool Apache NiFi to analyze and visualize data. Style and approach This step-by-step pragmatic guide will make life easy no matter what your level of experience. You will deep dive into Apache Spark on Hadoop clusters through ample exciting real-life examples. Practical tutorial explains data science in simple terms to help programmers and data analysts get started with Data Science

This book is a step-by-step tutorial filled with practical examples which will show readers how to configure and manage IaaS and DBaaS with Oracle Enterprise Manager. If you are a cloud administrator or a user of self-service provisioning systems offered by Enterprise Manager, this book is ideal for you. It will also help administrators who want to understand the chargeback mechanism offered by Enterprise Manager.An understanding of the basic building blocks of cloud computing such as networking, virtualization, storage, and so on, is needed by those of you interested in this book

It is in the context of maturity that one needs to read the book - Master Data Management and Enterprise Engineering by Dr. M. Naoulo. The world of technology has several related yet distinct approaches - Martin's and Finklestein's information engineering, Ted Codd's relational technology, Inmon's data warehouse, and others. This book takes these approaches and others and does two important things - it blends them together and it takes the bodies of thought and turns them into an engineering approach. As such this book is another important step in the evolution of computer science. This is a next step in the maturation of computer science. I recommend it to any serious student of computer science or to any serious practitioner. =========== W.H. (Bill) Inmon. May 21, 2012. =========== The book establishes the Fundamentals of design, modeling, architecture, and management of Master, Transactional, and Process Data and the Principles of Enterprise Engineering. The book comprises innovative techniques and elegant approach and design to address: > Master Data Management thru grouping and classifying the Master Data in an innovative way that can be implemented across the Enterprise Data Architecture: Central Data Repository and Business and Enterprise Intelligence (BI & EI) Data Marts. This data classification is based on the questions: Why, How, Who, What, Where and When. > Separating the Master Data, Transactional Data, and Process Data. This separation enables the easiness in dealing with MDM, BI, and EI. The separation approach enormously facilitates the mapping and propagation between the Central Data Repository and the Business and Enterprise Data Marts. >The basics and techniques of the design of the Enterprise Engineering Model. This model supports the Transactional Systems, Business Intelligence, Business Process Management, Enterprise Intelligence, and Enterprise Engineering. > Synchronization and Integration of Master, Transactional, and Process Data across the enterprise: Legacy Systems, Central Data Repository, and Business and Intelligence Data Marts. > Assessing the different Enterprise Data Architectures. The first part encompasses the Enterprise Data Framework and its new Modeling Techniques. The Enterprise Data Framework illustrates and depicts the Data Architecture across the enterprise covering the integration and consolidation of the data of the Legacy Systems in a Central Data Repository and the propagation of this data into the Business and Enterprise Intelligence Data Marts. The Enterprise Engineering Model presents a clear and concise illustration depicting the Operational aspects of the Enterprise and their relations to the Enterprise's needs. It includes: > Master Data representing the main objects of an enterprise, > Transactional Data detailing the results of transactions occurring in an enterprise, and > Process Data capturing the data pertinent to the activities of the functioning of an enterprise. The second part encompasses the Enterprise Engineering Framework, Methodology, Guidelines, Deliverables, and Techniques. It bestows the blueprint of the functioning of enterprises. This part details the basics of Enterprise Engineering and its implementation thru the processing of the Enterprise Engineering Model. It provides the cost data (materiel cost, labor cost, time) reflecting the functioning of the Enterprise and point out the efficiency, performance, strengths, and weaknesses of its operation. Detailed Case Studies are presented supporting the theoretical aspect of Enterprise Engineering. These Case Studies provide clear and practical hands-on exercises reflecting the functioning of the Enterprises and illustrating the implementation of Enterprise Engineering.

This book focuses on teaching you by example. The book walks you through every aspect of Pentaho Data Integration, giving systematic instructions in a friendly style, allowing you to learn in front of your computer, playing with the tool. The extensive use of drawings and screenshots make the process of learning Pentaho Data Integration easy. Throughout the book, numerous tips and helpful hints are provided that you will not find anywhere else.This book is a must-have for software developers, database administrators, IT students, and everyone involved or interested in developing ETL solutions, or, more generally, doing any kind of data manipulation. Those who have never used Pentaho Data Integration will benefit most from the book, but those who have, they will also find it useful.This book is also a good starting point for database administrators, data warehouse designers, architects, or anyone who is responsible for data warehouse projects and needs to load data into them.