This SpringerBrief reviews the knowledge engineering problem of engineering objectivity in top-k query answering; essentially, answers must be computed taking into account the user's preferences and a collection of (subjective) reports provided by other users. Most assume each report can be seen as a set of scores for a list of features, its author's preferences among the features, as well as other information is discussed in this brief. These pieces of information for every report are then combined, along with the querying user's preferences and their trust in each report, to rank the query results. Everyday examples of this setup are the online reviews that can be found in sites like Amazon, Trip Advisor, and Yelp, among many others. Throughout this knowledge engineering effort the authors adopt the Datalog+/- family of ontology languages as the underlying knowledge representation and reasoning formalism, and investigate several alternative ways in which rankings can b e derived, along with algorithms for top-k (atomic) query answering under these rankings. This SpringerBrief also investigate assumptions under which our algorithms run in polynomial time in the data complexity. Since this SpringerBrief contains a gentle introduction to the main building blocks (OBDA, Datalog+/-, and reasoning with preferences), it should be of value to students, researchers, and practitioners who are interested in the general problem of incorporating user preferences into related formalisms and tools. Practitioners also interested in using Ontology-based Data Access to leverage information contained in reviews of products and services for a better customer experience will be interested in this brief and researchers working in the areas of Ontological Languages, Semantic Web, Data Provenance, and Reasoning with Preferences.

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.

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.

Get up and running with the Pentaho Data Integration tool using this hands-on, easy-to-read guide About This Book * Manipulate your data by exploring, transforming, validating, and integrating it using Pentaho Data Integration 8 CE * A comprehensive guide exploring the features of Pentaho Data Integration 8 CE * Connect to any database engine, explore the databases, and perform all kind of operations on relational databases Who This Book Is For This book is a must-have for software developers, business intelligence analysts, IT students, or anyone involved or interested in developing ETL solutions. If you plan on using Pentaho Data Integration for doing any data manipulation task, this book will help you as well. This book is also a good starting point for data warehouse designers, architects, or anyone who is responsible for data warehouse projects and needs to load data into them. What You Will Learn * Explore the features and capabilities of Pentaho Data Integration 8 Community Edition * Install and get started with PDI * Learn the ins and outs of Spoon, the graphical designer tool * Learn to get data from all kind of data sources, such as plain files, Excel spreadsheets, databases, and XML files * Use Pentaho Data Integration to perform CRUD (create, read, update, and delete) operations on relationaldatabases * Populate a data mart with Pentaho Data Integration * Use Pentaho Data Integration to organize files and folders, run daily processes, deal with errors, and more In Detail Pentaho Data Integration(PDI) is an intuitive and graphical environment packed with drag-and-drop design and powerful Extract-Tranform-Load (ETL) capabilities. This book shows and explains the new interactive features of Spoon, the revamped look and feel, and the newest features of the tool including transformations and jobs Executors and the invaluable Metadata Injection capability. We begin with the installation of PDI software and then move on to cover all the key PDI concepts. Each of the chapter introduces new features, enabling you to gradually get practicing with the tool. First, you will learn to do all kind of data manipulation and work with simple plain files. Then, the book teaches you how you can work with relational databases inside PDI. Moreover, you will be given a primer on data warehouse concepts and you will learn how to load data in a data warehouse. During the course of this book, you will be familiarized with its intuitive, graphical and drag-and-drop design environment. By the end of this book, you will learn everything you need to know in order to meet your data manipulation requirements. Besides, your will be given best practices and advises for designing and deploying your projects. Style and approach Step by step guide filled with practical, real world scenarios and examples.

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.

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!

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.

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.

Technology has revolutionized the ways in which libraries store, share, and access information. As digital resources and tools continue to advance, so too do the opportunities for libraries to become more efficient and house more information. E-Discovery Tools and Applications in Modern Libraries presents critical research on the digitization of data and how this shift has impacted knowledge discovery, storage, and retrieval. This publication explores several emerging trends and concepts essential to electronic discovery, such as library portals, responsive websites, and federated search technology. The timely research presented within this publication is designed for use by librarians, graduate-level students, technology developers, and researchers in the field of library and information science.

This book introduces fundamentals and trade-offs of data de-duplication techniques. It describes novel emerging de-duplication techniques that remove duplicate data both in storage and network in an efficient and effective manner. It explains places where duplicate data are originated, and provides solutions that remove the duplicate data. It classifies existing de-duplication techniques depending on size of unit data to be compared, the place of de-duplication, and the time of de-duplication. Chapter 3 considers redundancies in email servers and a de-duplication technique to increase reduction performance with low overhead by switching chunk-based de-duplication and file-based de-duplication. Chapter 4 develops a de-duplication technique applied for cloud-storage service where unit data to be compared are not physical-format but logical structured-format, reducing processing time efficiently. Chapter 5 displays a network de-duplication where redundant data packets sent by clients are encoded (shrunk to small-sized payload) and decoded (restored to original size payload) in routers or switches on the way to remote servers through network. Chapter 6 introduces a mobile de-duplication technique with image (JPEG) or video (MPEG) considering performance and overhead of encryption algorithm for security on mobile device.

With this textbook, Vaisman and Zimanyi deliver excellent coverage of data warehousing and business intelligence technologies ranging from the most basic principles to recent findings and applications. To this end, their work is structured into three parts. Part I describes "Fundamental Concepts" including multi-dimensional models; conceptual and logical data warehouse design and MDX and SQL/OLAP. Subsequently, Part II details "Implementation and Deployment," which includes physical data warehouse design; data extraction, transformation, and loading (ETL) and data analytics. Lastly, Part III covers "Advanced Topics" such as spatial data warehouses; trajectory data warehouses; semantic technologies in data warehouses and novel technologies like Map Reduce, column-store databases and in-memory databases. As a key characteristic of the book, most of the topics are presented and illustrated using application tools. Specifically, a case study based on the well-known Northwind database illustrates how the concepts presented in the book can be implemented using Microsoft Analysis Services and Pentaho Business Analytics. All chapters are summarized using review questions and exercises to support comprehensive student learning. Supplemental material to assist instructors using this book as a course text is available at http://cs.ulb.ac.be/DWSDIbook/, including electronic versions of the figures, solutions to all exercises, and a set of slides accompanying each chapter. Overall, students, practitioners and researchers alike will find this book the most comprehensive reference work on data warehouses, with key topics described in a clear and educational style.

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.

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 presents Hyper-lattice, a new algebraic model for partially ordered sets, and an alternative to lattice. The authors analyze some of the shortcomings of conventional lattice structure and propose a novel algebraic structure in the form of Hyper-lattice to overcome problems with lattice. They establish how Hyper-lattice supports dynamic insertion of elements in a partial order set with a partial hierarchy between the set members. The authors present the characteristics and the different properties, showing how propositions and lemmas formalize Hyper-lattice as a new algebraic structure.