This book is your introduction in the world of graph databases, and the benefits they can bring to your applications. Neo4j is the most established graph database on the market, and it's always improving to bring more of its benefits to you. Beginning Neo4j will take you from the installation of Neo4j through to building a full application with Neo4j at its heart, and everything in between. Using this book, you'll get everything up and running, and then learn how to use Neo4j to build up recommendations, relationships, and calculate the shortest route between two locations. With example data models, and an application putting everything together, this book will give you everything you need to really get started with Neo4j. Neo4j is being used by social media and ecommerce industry giants. You can take advantage of Neo4j's powerful features and benefits - add Beginning Neo4j to your library today.

This book is a step-by-step guide for learning how to use Spark for different types of big-data analytics projects, including batch, interactive, graph, and stream data analysis as well as machine learning. It covers Spark core and its add-on libraries, including Spark SQL, Spark Streaming, GraphX, MLlib, and Spark ML. Big Data Analytics with Spark shows you how to use Spark and leverage its easy-to-use features to increase your productivity. You learn to perform fast data analysis using its in-memory caching and advanced execution engine, employ in-memory computing capabilities for building high-performance machine learning and low-latency interactive analytics applications, and much more. Moreover, the book shows you how to use Spark as a single integrated platform for a variety of data processing tasks, including ETL pipelines, BI, live data stream processing, graph analytics, and machine learning. The book also includes a chapter on Scala, the hottest functional programming language, and the language that underlies Spark. You’ll learn the basics of functional programming in Scala, so that you can write Spark applications in it. What's more, Big Data Analytics with Spark provides an introduction to other big data technologies that are commonly used along with Spark, such as HDFS, Avro, Parquet, Kafka, Cassandra, HBase, Mesos, and so on. It also provides an introduction to machine learning and graph concepts. So the book is self-sufficient; all the technologies that you need to know to use Spark are covered. The only thing that you are expected to have is some programming knowledge in any language.

This is a book for enterprise architects, database administrators, and developers who need to understand the latest developments in database technologies. It is the book to help you choose the correct database technology at a time when concepts such as Big Data, NoSQL and NewSQL are making what used to be an easy choice into a complex decision with significant implications. The relational database (RDBMS) model completely dominated database technology for over 20 years. Today this "one size fits all" stability has been disrupted by a relatively recent explosion of new database technologies. These paradigm-busting technologies are powering the "Big Data" and "NoSQL" revolutions, as well as forcing fundamental changes in databases across the board. Deciding to use a relational database was once truly a no-brainer, and the various commercial relational databases competed on price, performance, reliability, and ease of use rather than on fundamental architectures. Today we are faced with choices between radically different database technologies. Choosing the right database today is a complex undertaking, with serious economic and technological consequences. Next Generation Databases demystifies today’s new database technologies. The book describes what each technology was designed to solve. It shows how each technology can be used to solve real word application and business problems. Most importantly, this book highlights the architectural differences between technologies that are the critical factors to consider when choosing a database platform for new and upcoming projects. Introduces the new technologies that have revolutionized the database landscape Describes how each technology can be used to solve specific application or business challenges Reviews the most popular new wave databases and how they use these new database technologies

Master the SAP product ecosystem, the client environment, and the feasibility of implementing critical business process with the required technical and functional configuration. SAP Project Management Pitfalls is the first book to provide you with real examples of the pitfalls that you can avoid, providing you with a road-map to a successful implementation. Jay Kay, a SAP Program Manager for Capgemini, first takes a deep dive into common pitfalls in implementing SAP ERP projects in a complex IT landscape. You will learn about the potential causes of failures, study a selection of relevant project implementation case studies in the area, and see a range of possible countermeasures. Jay Kay also provides background on each - the significance of each implementation area, its relevance to a service company that implements SAP projects, and the current state of research. Key highlights of the book: Tools and techniques for project planning and templates for allocating resources Industry standards and innovations in SAP implementation projects in the form of standard solutions aimed at successful implementation Managing SAP system ECC upgrades, EHP updates and project patches Learn effective ways to implement robust SAP release management practices (change management, BAU) Wearing a practitioner’s insight, Jay Kay explores the relevance of each failed implementation scenario and how to support your company or clients to succeed in a SAP implementation. There are many considerations when implementing SAP, but as you will learn, knowledge, insight, and effective tools to mitigate risks can take you to a successful implementation project.

Dive into the world of geospatial analysis with Python in this comprehensive guide. This book will take you through the essentials of GIS, remote sensing, elevation data, and real-time data, all using Python. You will learn to analyze and visualize geospatial data effectively, building skills and understanding that are practical and relevant. What this Book will help me do Automate geospatial workflows using Python. Create thematic maps with Python tools for better spatial insights. Understand various forms of geospatial data and how to manage them. Develop GIS applications and elevation data models using minimal lines of Python code. Utilize Python for real-time data tracking and storm modeling. Author(s) Joel Lawhead is an experienced geospatial software developer and Python programmer with extensive expertise in GIS and geospatial data analysis. With a deep understanding of Python's applications in geography, Joel brings a practical focus to his writing. His engaging style ensures that technical concepts are accessible and thoroughly explained. Who is it for? This book is ideal for Python developers, researchers, and analysts who want to enhance their GIS and geospatial analysis capabilities. If you are familiar with Python or another scripting language and have a foundational understanding of digital mapping, this book will help you advance your knowledge and skills. Whether you're analyzing spatial data or building geospatial applications, this guide is made for you.

Statistics is the branch of mathematics that deals with real life problems. As such, it is an essential tool for economists. Unfortunately, the way the concept is introduced to students is not compatible with the way economists think and learn. The problem is worsened by the use of mathematical jargon and complex derivations. However, as this book demonstrates, neither is necessary. The book is written in simple English with minimal use of symbols, mostly for the sake of brevity and to make reading literature more meaningful. The second edition also incorporates Stata software for use by more technically oriented readers who have access to sophisticated software. The objective of this book is to address the fundamentals of statistical analysis in a simple and easy-to-comprehend way. Instead of covering numerous topics, the book covers interrelated subjects that are necessary for the comprehension of the presented topics. The second edition has augmented the explanations in the first to clarify the subjects even more. The examples are based on economic theory utilizing actual data. The hope is that the use of theory will prove useful in relating the subject to actual empirical applications and help with research.

Elasticsearch Indexing focuses on empowering developers to create optimized and user-friendly search experiences using Elasticsearch. By learning how to configure indices and mapping strategies, and leveraging analyzers effectively, you will gain proficiency in delivering fast and relevant search results tailored to modern user expectations. What this Book will help me do Understand how Elasticsearch stores data and how it reduces costs Develop advanced mapping strategies to improve index performance Utilize Elasticsearch analyzers for efficient search query processing Optimize ElasticSearch clusters for scalability and stability Perform strategic indexing to minimize resource usage while maximizing functionality Author(s) Huseyin Akdogan is a seasoned software developer specializing in search technologies and scalability. With his deep expertise and practical insights, he brings a metric-driven approach to optimizing Elasticsearch. His book reflects his dedication to making technical concepts accessible and actionable for developers. Who is it for? This book is ideal for developers looking to gain expertise in Elasticsearch. It caters to individuals with a foundational understanding of search systems who wish to optimize their indexing and search result delivery. If you are focused on improving user search experiences tailored to scalable needs, this book is perfect for you.

The quick way to learn Microsoft Visio 2016!This is learning made easy. Get more done quickly with Visio 2016. Jump in wherever you need answers--brisk lessons and colorful screenshots show you exactly what to do, step by step. Get results faster with starter diagrams Diagram processes, organizations, networks, and datacenters Add styles, colors, and themes Enhance diagrams with data-driven visualizations Link to external data sources, websites, and documents Add structure to diagrams with containers, lists, and callouts Validate flowchart, swimlane, and BPMN diagrams Collaborate and publish with Visio Services and Microsoft SharePoint 2016 Look up just the tasks and lessons you need

In The Patient Revolution, author Krisa Tailor—a noted expert in health care innovation and management—explores, through the lens of design thinking, how information technology will take health care into the experience economy. In the experience economy, patients will shift to being empowered consumers who are active participants in their own care. Tailor explores this shift by creating a vision for a newly designed health care system that's focused on both sickness and wellness, and is driven by data and analytics. The new system seamlessly integrates health into our daily lives, and delivers care so uniquely personalized that no two people are provided identical treatments. Connected through data, everyone across the health care ecosystem, including clinicians, insurers, and researchers, will be able to meet individuals wherever they are in their health journey to reach the ultimate goal of keeping people healthy. The patient revolution has just begun and an exciting journey awaits us. Praise for the patient revolution "A full 50% of the US population has at least one chronic disease that requires ongoing monitoring and treatment. Our current health care system is woefully inadequate in providing these individuals with the treatment and support they need. This disparity can only be addressed through empowering patients to better care for themselves and giving providers better tools to care for their patients. Both of those solutions will require the development and application of novel technologies. In Krisa Tailor's book The Patient Revolution, a blueprint is articulated for how this could be achieved, culminating in a vision for a learning health system within 10 years." —Ricky Bloomfield, MD, Director, Mobile Technology Strategy; Assistant Professor, Duke Medicine "In The Patient Revolution, Krisa Tailor astutely points out that 80% of health is impacted by factors outside of the health care system. Amazon unfortunately knows more about our patients than we do. The prescriptive analytics she describes will allow health care providers to use big data to optimize interventions at the level of the individual patient. The use of analytics will allow providers to improve quality, shape care coordination, and contain costs. Advanced analytics will lead to personalized care and ultimately empowered patients!" —Linda Butler, MD, Vice President of Medical Affairs/Chief Medical Officer/Chief Medical Information Officer, Rex Healthcare " The Patient Revolution provides a practical roadmap on how the industry can capture value by making health and care more personalized, anticipatory, and intuitive to patient needs." —Ash Damle, CEO, Lumiata "Excellent read. For me, health care represents a unique economy—one focused on technology, but requiring a deep understanding of humanity. Ms. Tailor begins the exploration of how we provide care via the concepts of design thinking, asking how we might redesign care with an eye toward changing the experience. She does an excellent job deconstructing this from the patient experience. I look forward to a hopeful follow-up directed at changing the provider culture." —Alan Pitt, MD, Chief Medical Officer, Avizia "Whether you're a health care provider looking to gain an understanding of the health care landscape, a health data scientist, or a seasoned business pro, you'll come away with a deeper, nuanced understanding of today's evolving health care system with this book. Krisa Tailor ties together—in a comprehensive, unique way—the worlds of health care administration, clinical practice, design thinking, and business strategy and innovation." —Steven Chan, MD, MBA, University of California, Davis

Build an enterprise search engine using Apache Solr: index and search documents; ingest data from varied sources; apply various text processing techniques; utilize different search capabilities; and customize Solr to retrieve the desired results. Apache Solr: A Practical Approach to Enterprise Search explains each essential concept--backed by practical and industry examples--to help you attain expert-level knowledge. The book, which assumes a basic knowledge of Java, starts with an introduction to Solr, followed by steps to setting it up, indexing your first set of documents, and searching them. It then introduces you to information retrieval and its implementation in Apache Solr; this will help you understand your search problem, decide the approach to build an effective solution, and use various metrics to evaluate the results. The book next covers the schema design and techniques to build a text analysis chain for cleansing, normalizing and enriching your documents and addressing different types of search queries. It describes various popular matching techniques which are generally applied to improve the precision and recall of searches. You will learn the end-to-end process of data ingestion from varied sources, metadata extraction, pre-processing and transformation of content, various search components, query parsers and other advanced search capabilities. After covering out-of-the-box features, Solr expert Dikshant Shahi dives into ways you can customize Solr for your business and its specific requirements, along with ways to plug in your own components. Most important, you will learn about implementations for Solr scoring, factors affecting the document score, and tuning the score for the application at hand. The book explains why textual scoring is not sufficient for practical ranking of documents and ways to integrate real-world factors for contributing to the document ranking. You'll see how to influence user experience by providing suggestions and recommendations. You'll also see integration of Solr with important related technologies such as OpenNLP and Tika. Additionally, you will learn about scaling Solr using SolrCloud. This book concludes with coverage of semantic search capabilities, which is crucial for taking the search experience to the next level. By the end of Apache Solr, you will be proficient in designing and developing your search engine.

Dive into the world of Apache Solr with this focused guide on indexing. Learn to harness Solr's powerful indexing features through real-world examples that help you efficiently fetch relevant data. From setting up Solr to mastering advanced techniques, this book ensures you are equipped to program and optimize Solr for a variety of applications. What this Book will help me do Gain a solid understanding of Solr indexing, analyzers, and tokenizers. Index diverse data sources, such as databases and documents, using Solr. Utilize Apache Tika to process PDFs and integrate Apache Nutch for web crawling. Implement distributed data indexing and facilitate real-time index updates. Apply learned indexing techniques to create robust solutions like e-commerce applications. Author(s) None Handiekar and None Johri are seasoned Apache Solr experts with years of practical experience. Having worked on diverse projects, they bring an enriched understanding of indexing and optimization. Their writing reflects a hands-on approach aimed at developers keen on mastering Solr effectively and efficiently. Who is it for? This book is designed for developers who are new to Solr yet aspire to deepen their understanding of its indexing capabilities. If you are interested in learning how to index using Solr's rich set of functionalities, this guide is for you. It provides practical steps for developers at an introductory level to start building more complex solutions. Perfect for developers eager to optimize their Solr indexing.

Learning RabbitMQ offers developers and system administrators a clear and practical guide to mastering RabbitMQ, the popular message-broker solution. By going through concrete scenarios and examples, this book equips you with the skills to configure, manage, and optimize RabbitMQ instances effectively. What this Book will help me do Understand and apply common messaging patterns using RabbitMQ. Set up and manage RabbitMQ clusters with high availability. Integrate RabbitMQ with popular tools like Spring, MuleESB, and Docker. Optimize RabbitMQ performance and ensure secure messaging. Troubleshoot and extend RabbitMQ for different use cases. Author(s) None Toshev, the author of Learning RabbitMQ, is an expert in middleware and distributed systems, with extensive hands-on experience working with message brokers. Toshev's practical approach and clear explanations make complex topics easy to understand, helping readers effectively apply best practices when using RabbitMQ. Who is it for? This book is for developers and system administrators who aim to incorporate RabbitMQ as part of their applications. Beginners with a basic understanding of messaging will find it foundational, while experienced users will appreciate the advanced insights on integration, performance tuning, and troubleshooting.

The W3C XQuery 3.1 standard provides a tool to search, extract, and manipulate content, whether it's in XML, JSON or plain text. With this fully updated, in-depth tutorial, you’ll learn to program with this highly practical query language. Designed for query writers who have some knowledge of XML basics, but not necessarily advanced knowledge of XML-related technologies, this book is ideal as both a tutorial and a reference. You’ll find background information for namespaces, schemas, built-in types, and regular expressions that are relevant to writing XML queries.

This brief book is a basic introduction to SQLite for iOS and Android developers. The book includes a simple introduction to SQL, a discussion of when to use SQLite, and chapters devoted to using SQLite with the most likely programming languages: Java, PHP, Swift and Objective-C. It then goes through adding simple database functionality to an Android or iOS app and finally a chapter on managing the app’s life cycle.

One of the most useful features of today’s modern browsers is the ability to store data right on the user’s computer or mobile device. Even as more people move toward the cloud, client-side storage can still save web developers a lot of time and money, if you do it right. This hands-on guide demonstrates several storage APIs in action. You’ll learn how and when to use them, their plusses and minuses, and steps for implementing one or more of them in your application.

This comprehensive guide to Qlik Sense provides you with everything you need to harness its data visualization capabilities effectively in your business or organization. Covering essential techniques and insights, this book focuses on understanding, implementing, and optimizing Qlik Sense for various data discovery applications. What this Book will help me do Understand the purpose and vision behind Qlik Sense and how it revolutionizes data discovery. Gain practical knowledge to manage, load, and visualize your data effectively using Qlik Sense. Learn how to administer Qlik Sense systems, ensuring secure and efficient usage. Explore extending Qlik Sense capabilities through its Dev Hub and other advanced features. Apply Qlik Sense in practical contexts, such as sales analytics, HR insights, and demographic studies. Author(s) Henric Cronström and co-authors, with vast experience directly from QlikTech International AB, bring authoritative insights into this book. Their expertise in business analytics and direct involvement with the development of Qlik Sense make this book a reliable and insightful resource for learners. Who is it for? This book is ideal for business intelligence professionals, data analysts, and decision-makers looking to maximize the potential of Qlik Sense. Whether you're new to Qlik Sense or have a general understanding of BI concepts, this guide will help you elevate your data discovery skills and apply actionable insights to real-world scenarios.

Master Data Analytics Hands-On by Solving Fascinating Problems You’ll Actually Enjoy! Harvard Business Review recently called data science “The Sexiest Job of the 21st Century.” It’s not just sexy: For millions of managers, analysts, and students who need to solve real business problems, it’s indispensable. Unfortunately, there’s been nothing easy about learning data science–until now. Getting Started with Data Science takes its inspiration from worldwide best-sellers like Freakonomics and Malcolm Gladwell’s Outliers: It teaches through a powerful narrative packed with unforgettable stories. Murtaza Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. Everything’s software and platform agnostic, so you can learn data science whether you work with R, Stata, SPSS, or SAS. Best of all, Haider teaches a crucial skillset most data science books ignore: how to tell powerful stories using graphics and tables. Every chapter is built around real research challenges, so you’ll always know why you’re doing what you’re doing. You’ll master data science by answering fascinating questions, such as: • Are religious individuals more or less likely to have extramarital affairs? • Do attractive professors get better teaching evaluations? • Does the higher price of cigarettes deter smoking? • What determines housing prices more: lot size or the number of bedrooms? • How do teenagers and older people differ in the way they use social media? • Who is more likely to use online dating services? • Why do some purchase iPhones and others Blackberry devices? • Does the presence of children influence a family’s spending on alcohol? For each problem, you’ll walk through defining your question and the answers you’ll need; exploring how others have approached similar challenges; selecting your data and methods; generating your statistics; organizing your report; and telling your story. Throughout, the focus is squarely on what matters most: transforming data into insights that are clear, accurate, and can be acted upon.

Practical Guide to MongoDB: Architecting, Developing, and Administering MongoDB begins with a short introduction to the basics of NoSQL databases and then introduces readers to MongoDB—the leading document based NoSQL database, acquainting them step-by-step with all aspects of MongoDB. Practical Guide to MongoDB covers the data model, underlying architecture, coding with Mongo Shell, and administrating the MongoDB platform, among other topics. The book also provides clear guidelines and practical examples for architecting, developing, and deploying applications using the MongoDB platform. Database developers, architects, and administrators will find useful information covering all aspects of the MongoDB platform and how to put it to use practically. The "one-size-fits-all" thinking regarding traditional RDBMSs has been challenged in the last few years by the emergence of diversified NoSQL databases. More than 120 NoSQL databases are now available in the market, and the leader by far is MongoDB. With so many companies opting for MongoDB as their NoSQL database of choice, there's a need for a practical how-to combined with expert advice for getting the most out of the software. Practical Guide to MongoDB provides readers with: A solid understanding of NoSQL databases An understanding of how to get started with MongoDB Methodical coverage of the architecture, development, and administration of MongoDB A plethora of "How to’s" enabling you to use the technology most efficiently to solve the problems you face

In just 24 lessons of one hour or less, Sams Teach Yourself R in 24 Hours helps you learn all the R skills you need to solve a wide spectrum of real-world data analysis problems. You’ll master the entire data analysis workflow, learning to build code that’s efficient, reproducible, and suitable for sharing with others. This book’s straightforward, step-by-step approach teaches you how to import, manipulate, summarize, model, and plot data with R; formalize your analytical code; and build powerful R packages using current best practices. Practical, hands-on examples show you how to apply what you learn. Quizzes and exercises help you test your knowledge and stretch your skills. Learn How To Install, configure, and explore the R environment, including RStudio Use basic R syntax, objects, and packages Create and manage data structures, including vectors, matrices, and arrays Understand lists and data frames Work with dates, times, and factors Use common R functions, and learn to write your own Import and export data and connect to databases and spreadsheets Use the popular tidyr, dplyr and data.table packages Write more efficient R code with profiling, vectorization, and initialization Plot data and extend your graphical capabilities with ggplot2 and Lattice graphics Develop common types of models Construct high-quality packages, both simple and complex Write R classes: S3, S4, and Reference Classes Use R to generate dynamic reports Build web applications with Shiny Register your book at informit.com/register for convenient access to updates and corrections as they become available. This book’s source code can be found at http://www.mango-solutions.com/wp/teach-yourself-r-in-24-hours-book/.

Integrate big data into business to drive competitive advantage and sustainable success Big Data MBA brings insight and expertise to leveraging big data in business so you can harness the power of analytics and gain a true business advantage. Based on a practical framework with supporting methodology and hands-on exercises, this book helps identify where and how big data can help you transform your business. You'll learn how to exploit new sources of customer, product, and operational data, coupled with advanced analytics and data science, to optimize key processes, uncover monetization opportunities, and create new sources of competitive differentiation. The discussion includes guidelines for operationalizing analytics, optimal organizational structure, and using analytic insights throughout your organization's user experience to customers and front-end employees alike. You'll learn to “think like a data scientist” as you build upon the decisions your business is trying to make, the hypotheses you need to test, and the predictions you need to produce. Business stakeholders no longer need to relinquish control of data and analytics to IT. In fact, they must champion the organization's data collection and analysis efforts. This book is a primer on the business approach to analytics, providing the practical understanding you need to convert data into opportunity. Understand where and how to leverage big data Integrate analytics into everyday operations Structure your organization to drive analytic insights Optimize processes, uncover opportunities, and stand out from the rest Help business stakeholders to “think like a data scientist” Understand appropriate business application of different analytic techniques If you want data to transform your business, you need to know how to put it to use. Big Data MBA shows you how to implement big data and analytics to make better decisions.