Customer and Business Analytics, Putler, Daniel S.
Автор: Teresa Torres, Torres Название: Continuous discovery habits ISBN: 1736633309 ISBN-13(EAN): 9781736633304 Издательство: Неизвестно Рейтинг: Цена: 18380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: These early stories by the award-winning novelist, David Allan Cates, take place in Mexico and Central America during the war years of the 1980s. The protagonists are exiled lovers-broken for the most part and trying to make sense of their new world of grief. Far from home and working in a boatyard, on a movie set, a banana freighter, as a veal salesman, medical interpreter, writer, and Sandinista volunteer, they`re forced to re-imagine not only love, peace, suffering, and beauty but the meaning of their very own lives. "The stories in David Allan Cates`s Imagining Tanya, sometimes harrowing, sometimes hilarious, are always moving. Like his novels, they`re the perfect mixture of tough and tender, full of heart, mystery, and wisdom. But the compressed form allows him to focus on the strange, subtle moments that turn a life upside down or right it again, even if his characters don`t always recognize the change when it comes. In these rich pages, a host of American ex-pats wandering in Central America-some innocent, some jaded-all carry with them the potential for an earthly, messy sort of grace, gifted to them by a masterful storyteller." - Scott Nadelson, author of One of Us and The Next Scott Nadelson "David Allan Cates creates a vivid, unforgettable world of souls lost in Central America in the 1980s. The characters` heartbreak and displacement are mirrored by the larger conflicts of war all around them, and they seek redemption in the bravery of loving through pain. Imagining Tanya is a bold, gripping, and seductive collection, full of moments of grace." - Maxim Loskutoff, author of Ruthie Fear and Come West and See
Автор: Soofastaei Ali Название: Advanced Analytics in Mining Engineering: Leverage Advanced Analytics in Mining Industry to Make Better Business Decisions ISBN: 3030915883 ISBN-13(EAN): 9783030915889 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In this book, Dr. Soofastaei and his colleagues reveal how all mining managers can effectively deploy advanced analytics in their day-to-day operations- one business decision at a time. Most mining companies have a massive amount of data at their disposal. However, they cannot use the stored data in any meaningful way. The powerful new business tool-advanced analytics enables many mining companies to aggressively leverage their data in key business decisions and processes with impressive results. From statistical analysis to machine learning and artificial intelligence, the authors show how many analytical tools can improve decisions about everything in the mine value chain, from exploration to marketing. Combining the science of advanced analytics with the mining industrial business solutions, introduce the “Advanced Analytics in Mining Engineering Book” as a practical road map and tools for unleashing the potential buried in your company’s data. The book is aimed at providing mining executives, managers, and research and development teams with an understanding of the business value and applicability of different analytic approaches and helping data analytics leads by giving them a business framework in which to assess the value, cost, and risk of potential analytical solutions. In addition, the book will provide the next generation of miners – undergraduate and graduate IT and mining engineering students – with an understanding of data analytics applied to the mining industry. By providing a book with chapters structured in line with the mining value chain, we will provide a clear, enterprise-level view of where and how advanced data analytics can best be applied. This book highlights the potential to interconnect activities in the mining enterprise better. Furthermore, the book explores the opportunities for optimization and increased productivity offered by better interoperability along the mining value chain – in line with the emerging vision of creating a digital mine with much-enhanced capabilities for modeling, simulation, and the use of digital twins – in line with leading “digital” industries.
Автор: Jones Herbert Название: Data Science for Business: Predictive Modeling, Data Mining, Data Analytics, Data Warehousing, Data Visualization, Regression Analysis, Database ISBN: 1647483263 ISBN-13(EAN): 9781647483265 Издательство: Неизвестно Рейтинг: Цена: 27580.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Data science has a huge impact on how companies conduct business, and those who don`t learn about this revolutionaryfield could be left behind. You see, data science will help you make better decisions, know what products and services to release, and how to provide better service to your customers.
Автор: Katarzyna Tarnowska; Zbigniew W. Ras; Lynn Daniel Название: Recommender System for Improving Customer Loyalty ISBN: 3030134377 ISBN-13(EAN): 9783030134372 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents the Recommender System for Improving Customer Loyalty. New and innovative products have begun appearing from a wide variety of countries, which has increased the need to improve the customer experience. When a customer spends hundreds of thousands of dollars on a piece of equipment, keeping it running efficiently is critical to achieving the desired return on investment. Moreover, managers have discovered that delivering a better customer experience pays off in a number of ways. A study of publicly traded companies conducted by Watermark Consulting found that from 2007 to 2013, companies with a better customer service generated a total return to shareholders that was 26 points higher than the S&P 500. This is only one of many studies that illustrate the measurable value of providing a better service experience.
The Recommender System presented here addresses several important issues. (1) It provides a decision framework to help managers determine which actions are likely to have the greatest impact on the Net Promoter Score. (2) The results are based on multiple clients. The data mining techniques employed in the Recommender System allow users to “learn” from the experiences of others, without sharing proprietary information. This dramatically enhances the power of the system. (3) It supplements traditional text mining options. Text mining can be used to identify the frequency with which topics are mentioned, and the sentiment associated with a given topic. The Recommender System allows users to view specific, anonymous comments associated with actual customers. Studying these comments can provide highly accurate insights into the steps that can be taken to improve the customer experience. (4) Lastly, the system provides a sensitivity analysis feature. In some cases, certain actions can be more easily implemented than others. The Recommender System allows managers to “weigh” these actions and determine which ones would have a greater impact.
Автор: Hofmann Markus Название: RapidMiner ISBN: 1482205491 ISBN-13(EAN): 9781482205497 Издательство: Taylor&Francis Рейтинг: Цена: 84710.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Powerful, Flexible Tools for a Data-Driven WorldAs the data deluge continues in today’s world, the need to master data mining, predictive analytics, and business analytics has never been greater. These techniques and tools provide unprecedented insights into data, enabling better decision making and forecasting, and ultimately the solution of increasingly complex problems. Learn from the Creators of the RapidMiner Software Written by leaders in the data mining community, including the developers of the RapidMiner software, RapidMiner: Data Mining Use Cases and Business Analytics Applications provides an in-depth introduction to the application of data mining and business analytics techniques and tools in scientific research, medicine, industry, commerce, and diverse other sectors. It presents the most powerful and flexible open source software solutions: RapidMiner and RapidAnalytics. The software and their extensions can be freely downloaded at www.RapidMiner.com. Understand Each Stage of the Data Mining ProcessThe book and software tools cover all relevant steps of the data mining process, from data loading, transformation, integration, aggregation, and visualization to automated feature selection, automated parameter and process optimization, and integration with other tools, such as R packages or your IT infrastructure via web services. The book and software also extensively discuss the analysis of unstructured data, including text and image mining. Easily Implement Analytics Approaches Using RapidMiner and RapidAnalytics Each chapter describes an application, how to approach it with data mining methods, and how to implement it with RapidMiner and RapidAnalytics. These application-oriented chapters give you not only the necessary analytics to solve problems and tasks, but also reproducible, step-by-step descriptions of using RapidMiner and RapidAnalytics. The case studies serve as blueprints for your own data mining applications, enabling you to effectively solve similar problems.
Автор: Fridolin Wild Название: Learning Analytics in R with SNA, LSA, and MPIA ISBN: 3319287893 ISBN-13(EAN): 9783319287898 Издательство: Springer Рейтинг: Цена: 88500.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book introduces Meaningful Purposive Interaction Analysis (MPIA) theory, which combines social network analysis (SNA) with latent semantic analysis (LSA) to help create and analyse a meaningful learning landscape from the digital traces left by a learning community in the co-construction of knowledge.
Автор: Prajapati, Vignesh Название: Big data analytics with r and hadoop ISBN: 178216328X ISBN-13(EAN): 9781782163282 Издательство: Неизвестно Рейтинг: Цена: 45970.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
If you're an R developer looking to harness the power of big data analytics with Hadoop, then this book tells you everything you need to integrate the two. You'll end up capable of building a data analytics engine with huge potential.
About This Book
Write Hadoop MapReduce within R
Learn data analytics with R and the Hadoop platform
Handle HDFS data within R
Understand Hadoop streaming with R
Encode and enrich datasets into R
In Detail
Big data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations, and other useful information. Such information can provide competitive advantages over rival organizations and result in business benefits, such as more effective marketing and increased revenue. New methods of working with big data, such as Hadoop and MapReduce, offer alternatives to traditional data warehousing.
Big Data Analytics with R and Hadoop is focused on the techniques of integrating R and Hadoop by various tools such as RHIPE and RHadoop. A powerful data analytics engine can be built, which can process analytics algorithms over a large scale dataset in a scalable manner. This can be implemented through data analytics operations of R, MapReduce, and HDFS of Hadoop.
You will start with the installation and configuration of R and Hadoop. Next, you will discover information on various practical data analytics examples with R and Hadoop. Finally, you will learn how to import/export from various data sources to R. Big Data Analytics with R and Hadoop will also give you an easy understanding of the R and Hadoop connectors RHIPE, RHadoop, and Hadoop streaming.
What You Will Learn
Integrate R and Hadoop via RHIPE, RHadoop, and Hadoop streaming
Develop and run a MapReduce application that runs with R and Hadoop
Handle HDFS data from within R using RHIPE and RHadoop
Run Hadoop streaming and MapReduce with R
Import and export from various data sources to R
Автор: Andrade Название: Fundamentals of Stream Processing ISBN: 1107015545 ISBN-13(EAN): 9781107015548 Издательство: Cambridge Academ Рейтинг: Цена: 91870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book teaches fundamentals of the stream processing paradigm that addresses performance, scalability and usability challenges in extracting insights from massive amounts of live, streaming data. It presents core principles behind application design, system infrastructure and analytics, coupled with real-world examples for a comprehensive understanding of the stream processing area.
Автор: Ulf Brefeld; Jesse Davis; Jan Van Haaren; Albrecht Название: Machine Learning and Data Mining for Sports Analytics ISBN: 3030172732 ISBN-13(EAN): 9783030172732 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed post-conference proceedings of the 5th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2018, colocated with ECML/PKDD 2018, in Dublin, Ireland, in September 2018.
The 12 full papers presented together with 4 challenge papers were carefully reviewed and selected from 24 submissions. The papers present a variety of topics, covering the team sports American football, basketball, ice hockey, and soccer, as well as the individual sports cycling and martial arts. In addition, four challenge papers are included, reporting on how to predict pass receivers in soccer.
Автор: Albert Ali Salah; Alex Pentland; Bruno Lepri; Emma Название: Guide to Mobile Data Analytics in Refugee Scenarios ISBN: 303012553X ISBN-13(EAN): 9783030125530 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Поставка под заказ. Описание: After the start of the Syrian Civil War in 2011–12, increasing numbers of civilians sought refuge in neighboring countries. By May 2017, Turkey had received over 3 million refugees — the largest refugee population in the world. Some lived in government-run camps near the Syrian border, but many have moved to cities looking for work and better living conditions. They faced problems of integration, income, welfare, employment, health, education, language, social tension, and discrimination. In order to develop sound policies to solve these interlinked problems, a good understanding of refugee dynamics isnecessary.This book summarizes the most important findings of the Data for Refugees (D4R) Challenge, which was a non-profit project initiated to improve the conditions of the Syrian refugees in Turkey by providing a database for the scientific community to enable research on urgent problems concerning refugees. The database, based on anonymized mobile call detail records (CDRs) of phone calls and SMS messages of one million Turk Telekom customers, indicates the broad activity and mobility patterns of refugees and citizens in Turkey for the year 1 January to 31 December 2017. Over 100 teams from around the globe applied to take part in the challenge, and 61 teams were granted access to the data.This book describes the challenge, and presents selected and revised project reports on the five major themes: unemployment, health, education, social integration, and safety, respectively. These are complemented by additional invited chapters describing related projects from international governmental organizations, technological infrastructure, as well as ethical aspects. The last chapter includes policy recommendations, based on the lessons learned.The book will serve as a guideline for creating innovative data-centered collaborations between industry, academia, government, and non-profit humanitarian agencies to deal with complex problems in refugee scenarios. It illustrates the possibilities of big data analytics in coping with refugee crises and humanitarian responses, by showcasing innovative approaches drawing on multiple data sources, information visualization, pattern analysis, and statistical analysis.It will also provide researchers and students working with mobility data with an excellent coverage across data science, economics, sociology, urban computing, education, migration studies, and more.
Автор: Wei Lee Woon; Zeyar Aung; Alejandro Catalina Feli? Название: Data Analytics for Renewable Energy Integration. Technologies, Systems and Society ISBN: 3030043029 ISBN-13(EAN): 9783030043025 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the revised selected papers from the 6th ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2018, held in Dublin, Ireland, in September 2018.The 9 papers presented in this volume were carefully reviewed and selected for inclusion in this book and handle topics such as time series forecasting, the detection of faults, cyber security, smart grid and smart cities, technology integration, demand response, and many others.
Автор: Prasant Kumar Pattnaik; Raghvendra Kumar; Souvik P Название: IoT and Analytics for Agriculture ISBN: 9811391769 ISBN-13(EAN): 9789811391767 Издательство: Springer Рейтинг: Цена: 158380.00 T Наличие на складе: Поставка под заказ. Описание: This book presents recent findings on virtually every aspect of wireless IoT and analytics for agriculture. It discusses IoT-based monitoring systems for analyzing the crop environment, and methods for improving the efficiency of decision-making based on the analysis of harvest statistics. In turn, it addresses the latest innovations, trends, and concerns, as well as practical challenges encountered and solutions adopted in the fields of IoT and analytics for agriculture. In closing, it explores a range of applications, including: intelligent field monitoring, intelligent data processing and sensor technologies, predictive analysis systems, crop monitoring, and weather data-enabled analysis in IoT agro-systems.
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