Dieses neuartige Lehrbuch gibt den Studierenden der neuen Masterstudiengange in zwolf Lern- und Arbeitsmodulen die Grundlage fur einen sicheren Studien- und Prufungserfolg. Der Studierende wird nicht mit Wissen zugeschuttet, sondern kann sich auf der Grundlage einer sehr guten Ubersicht alle relevanten Themengebiete selbststandig erarbeiten. Die Module sind alle gleichermassen aufgebaut. Ausgehend von bestehendem Grundwissen werden exemplarisch Aufgabenstellungen vorgestellt, die vom Leser sukzessive gelost werden. Tests, Projektarbeiten, Fallstudien und weitere Aufgaben unterstutzen den Selbstlern-Effekt. Das Buch zeichnet sich durch ein hohes Mass an Verstandlichkeit und Praxisnahe aus. Ein Buch, das den Leser an die Hand nimmt, ohne ihn zu bevormunde

Since long before computers were even thought of, data has been collected and organized by diverse cultures across the world. Once access to the Internet became a reality for large swathes of the world's population, the amount of data generated each day became huge, and continues to grow exponentially. It includes all our uploaded documents, video, and photos, all our social media traffic, our online shopping, even the GPS data from our cars. 'Big Data' represents a qualitative change, not simply a quantitative one. The term refers both to the new technologies involved, and to the way it can be used by business and government. Dawn E. Holmes uses a variety of case studies to explain how data is stored, analysed, and exploited by a variety of bodies from big companies to organizations concerned with disease control. Big data is transforming the way businesses operate, and the way medical research can be carried out. At the same time, it raises important ethical issues; Holmes discusses cases such as the Snowden affair, data security, and domestic smart devices which can be hijacked by hackers. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.

What are your organization's policies for generating and using huge datasets full of personal information? This book examines ethical questions raised by the big data phenomenon, and explains why enterprises need to reconsider business decisions concerning privacy and identity. Authors Kord Davis and Doug Patterson provide methods and techniques to help your business engage in a transparent and productive ethical inquiry into your current data practices.

Both individuals and organizations have legitimate interests in understanding how data is handled. Your use of data can directly affect brand quality and revenue--as Target, Apple, Netflix, and dozens of other companies have discovered. With this book, you'll learn how to align your actions with explicit company values and preserve the trust of customers, partners, and stakeholders.Review your data-handling practices and examine whether they reflect core organizational valuesExpress coherent and consistent positions on your organization's use of big dataDefine tactical plans to close gaps between values and practices--and discover how to maintain alignment as conditions change over timeMaintain a balance between the benefits of innovation and the risks of unintended consequences

BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen Data analysis is a scientific field that continues to grow enormously, most notably over the last few decades, following rapid growth within the tech industry, as well as the wide applicability of computational techniques alongside new advances in analytic tools. Modeling enables data analysts to identify relationships, make predictions, and to understand, interpret and visualize the extracted information more strategically. This book includes the most recent advances on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 1 is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians, working on the front end of data analysis and modeling applications. The chapters cover a cross section of current concerns and research interests in the above scientific areas. The collected material is divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications.

It is not lost on commercial organisations that where we live colours how we view ourselves and others. That is why so many now place us into social groups on the basis of the type of postcode in which we live. Social scientists call this practice "commercial sociology". Richard Webber originated Acorn and Mosaic, the two most successful geodemographic classifications. Roger Burrows is a critical interdisciplinary social scientist. Together they chart the origins of this practice and explain the challenges it poses to long-established social scientific beliefs such as: the role of the questionnaire in an era of "big data" the primacy of theory the relationship between qualitative and quantitative modes of understanding the relevance of visual clues to lay understanding. To help readers evaluate the validity of this form of classification, the book assesses how well geodemographic categories track the emergence of new types of residential neighbourhood and subject a number of key contemporary issues to geodemographic modes of analysis.

Enterprise Resource Planning (ERP), Supply Chain Management (SCM), Customer Relationship Management (CRM), Business Intelligence (BI) und Big Data Analytics (BDA) sind unternehmerische Aufgaben und Prozesse, die durch standardisierte Softwareloesungen unterstutzt werden.Dieses Lehrbuch lasst Studierende direkt aus der Businessperspektive anhand eines rollenbasierten Business Games erfahren, wie unternehmerische Aufgaben und Prozesse mit Hilfe standardisierter Softwaresysteme realisiert werden. Dadurch vermittelt es managementorientiertes Denken und Handeln, das fur Informatiker, die sich mit geschaftsprozessorientierten IT-Loesungen befassen, unerlasslich ist.Die dritte Auflage des Buches wurde vollstandig uberarbeitet, neu strukturiert und um aktuelle Themenbereiche wie Blockchains in der Supply Chain und die Beziehung von Big Data Analytics zu Artificial Intelligence und Machine Learning erganzt. Die Struktur des Buches orientiert sich an der schrittweisen Implementierung und Integration der jeweiligen Informationssysteme aus Unternehmens-, Business-, und Managementsicht. Teil I enthalt ausfuhrliche Kapitel zu den behandelten Themen mit Online-Tests und -UEbungen zu jedem Kapitel. Teil II fuhrt in das Rollenspiel und in die Online-Gaming- und Simulationsumgebung ein. Erganzendes Unterrichtsmaterial, Prasentationen, Templates und Videoclips stehen online im Gamingbereich zur Verfugung. Die fur dieses Buch neu geschaffene Gaming- und Businesssimulation Kdibisglobal.com enthalt neben der bisherigen Bier-Division neu eine Mineral- und Tafelwasser-Division, eine Soft-Drink-Division sowie ein Fertigungsunternehmen fur Barcode-Kassensysteme mit ihren speziellen Geschaftsprozessen und Supply Chains.

The Cognitive Approach in Cloud Computing and Internet of Things Technologies for Surveillance Tracking Systems discusses the recent, rapid development of Internet of things (IoT) and its focus on research in smart cities, especially on surveillance tracking systems in which computing devices are widely distributed and huge amounts of dynamic real-time data are collected and processed. Efficient surveillance tracking systems in the Big Data era require the capability of quickly abstracting useful information from the increasing amounts of data. Real-time information fusion is imperative and part of the challenge to mission critical surveillance tasks for various applications. This book presents all of these concepts, with a goal of creating automated IT systems that are capable of resolving problems without demanding human aid.

Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data. Machine learning and parallel computing are increasingly becoming cross-disciplinary as the phenomena of Big Data is becoming common place. This book provides insight into the common workflows and data science tools used for big data in astronomy and geoscience. After establishing similarity in data gathering, pre-processing and handling, the data science aspects are illustrated in the context of both fields. Software, hardware and algorithms of big data are addressed. Finally, the book offers insight into the emerging science which combines data and expertise from both fields in studying the effect of cosmos on the earth and its inhabitants.

Design, create and manage robust Power BI solutions to gain meaningful business insights Key Features Master all the dashboarding and reporting features of Microsoft Power BI Combine data from multiple sources, create stunning visualizations and publish your reports across multiple platforms A comprehensive guide with real-world use cases and examples demonstrating how you can get the best out of Microsoft Power BI Book DescriptionThis book is intended for business intelligence professionals responsible for the design and development of Power BI content as well as managers, architects and administrators who oversee Power BI projects and deployments. The chapters flow from the planning of a Power BI project through the development and distribution of content to the administration of Power BI for an organization. BI developers will learn how to create sustainable and impactful Power BI datasets, reports, and dashboards. This includes connecting to data sources, shaping and enhancing source data, and developing an analytical data model. Additionally, top report and dashboard design practices are described using features such as Bookmarks and the Power KPI visual. BI managers will learn how Power BI's tools work together such as with the On-premises data gateway and how content can be staged and securely distributed via Apps. Additionally, both the Power BI Report Server and Power BI Premium are reviewed. By the end of this book, you will be confident in creating effective charts, tables, reports or dashboards for any kind of data using the tools and techniques in Microsoft Power BI. What you will learn Build efficient data retrieval and transformation processes with the Power Query M Language Design scalable, user-friendly DirectQuery and Import Data Models Develop visually rich, immersive, and interactive reports and dashboards Maintain version control and stage deployments across development, test, and production environments Manage and monitor the Power BI Service and the On-premises data gateway Develop a fully on-premise solution with the Power BI Report Server Scale up a Power BI solution via Power BI Premium capacity and migration to Azure Analysis Services or SQL Server Analysis Services Who this book is forBusiness Intelligence professionals and existing Power BI users looking to master Power BI for all their data visualization and dashboarding needs will find this book to be useful. While understanding of the basic BI concepts is required, some exposure to Microsoft Power BI will be helpful.

Although some IoT systems are built for simple event control where a sensor signal triggers a corresponding reaction, many events are far more complex, requiring applications to interpret the event using analytical techniques to initiate proper actions. Artificial intelligence of things (AIoT) applies intelligence to the edge and gives devices the ability to understand the data, observe the environment around them, and decide what to do best with minimum human intervention. With the power of AI, AIoT devices are not just messengers feeding information to control centers. They have evolved into intelligent machines capable of performing self-driven analytics and acting independently. A smart environment uses technologies such as wearable devices, IoT, and mobile internet to dynamically access information, connect people, materials and institutions, and then actively manages and responds to the ecosystem's needs in an intelligent manner. In this edited book, the authors present challenges, technologies, applications and future trends of AI-enabled IoT (AIoT) in realizing smart and intelligent environments, including frameworks and methodologies to apply AIoT in monitoring devices and environments, tools and practices most applicable to product or service development to solve innovation problems, advanced and innovative techniques and practical implementations to enhance future smart environment systems as. They plan to cover a broad range of applications including smart cities, smart transportation and smart agriculture. This book is a valuable resource for industry and academic researchers, scientists, engineers and advanced students in the fields of ICTs and networking, IoT, AI and machine and deep learning, data science, sensing, robotics, automation and smart technologies and smart environments.

Dieses Buch bietet einen historisch orientierten Einstieg in die elementare Zahlentheorie. Es stellt eine solide Basis fur vielfaltige Ausbaumoeglichkeiten dar. Besondere Zielsetzungen sind: Elementaritat und Anschaulichkeit, die Berucksichtigung der historischen Entwicklung, Motivation der Begriffe und Verfahren anhand konkreter, aussagekraftiger Beispiele unter Einbezug moderner Werkzeuge (Computeralgebra Systeme, Internet). Als Zusatzmedien werden Computer- und Internet-spezifische Interaktions- und Visualisierungsmoeglichkeiten (kostenlos) zur Verfugung gestellt. Das Werk wendet sich an Studierende (Bachelor/Lehramt), Lehrer(innen) sowie alle an Elementarmathematik interessierten Leser.

Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics. This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management.

Das Buch beinhaltet die Ergebnisse des dreijahrigen Verbundprojekts Separator i4.0 des BMBF-Spitzenclusters it's OWL. Gegenstand des Projekts war die nachhaltige Einbindung von Expertenwissen in die zukunftsweisende Weiterentwicklung und Optimierung von Separationsprozessen. Durch die Entwicklung neuartiger intelligenter Komponenten aus dem Bereich der Sensorik wird es zukunftig moeglich sein, Separatoren und die zugehoerigen Prozesszusammenhange zu verstehen und diese oekologisch/oekonomisch optimal auszulegen und zu betreiben. Hierzu wurde ein Instrumentarium bestehend aus Methoden und Loesungen erarbeitet, das daruber hinaus auf analoge Problemstellungen komplexer maschinenbaulicher Anlagen anwendbar sein wird.

Von namhaften Professoren empfohlen: State-of-the-Art bietet das Buch zu diesem klassischen Bereich der Informatik. Die wesentlichen Methoden wissensbasierter Systeme werden verstandlich und anschaulich dargestellt. Reprasentation und Verarbeitung sicheren und unsicheren Wissens in maschinellen Systemen stehen dabei im Mittelpunkt. Ein Online-Service mit ausfuhrlichen Musterloesungen erleichtert das Lernen.

Meta-Analytics: Consensus Approaches and System Patterns for Data Analysis presents an exhaustive set of patterns for data science to use on any machine learning based data analysis task. The book virtually ensures that at least one pattern will lead to better overall system behavior than the use of traditional analytics approaches. The book is 'meta' to analytics, covering general analytics in sufficient detail for readers to engage with, and understand, hybrid or meta- approaches. The book has relevance to machine translation, robotics, biological and social sciences, medical and healthcare informatics, economics, business and finance. Inn addition, the analytics within can be applied to predictive algorithms for everyone from police departments to sports analysts.

Intelligent Data Analysis for Biomedical Applications: Challenges and Solutions presents specialized statistical, pattern recognition, machine learning, data abstraction and visualization tools for the analysis of data and discovery of mechanisms that create data. It provides computational methods and tools for intelligent data analysis, with an emphasis on problem-solving relating to automated data collection, such as computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and more. This book provides useful references for educational institutions, industry professionals, researchers, scientists, engineers and practitioners interested in intelligent data analysis, knowledge discovery, and decision support in databases.

What if you could peer into the minds of an entire population? What if you could target the weakest with rumours that only they saw?

In 2016, an obscure British military contractor turned the world upside down. Funded by a billionaire on a crusade to start his own far-right insurgency, Cambridge Analytica combined psychological research with private Facebook data to make an invisible weapon with the power to change what voters perceived as real.

The firm was created to launch the then unknown Steve Bannon's ideological assault on America. But as it honed its dark arts in elections from Trinidad to Nigeria, 24-year-old research director Christopher Wylie began to see what he and his colleagues were unleashing.

He had heard the disturbing visions of the investors. He saw what CEO Alexander Nix did behind closed doors. When Britain shocked the world by voting to leave the EU, Wylie realised it was time to expose his old associates. The political crime of the century had just taken place - the weapon had been tested - and nobody knew.

Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Science has become an essential tool to extract value from data for any organization that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, engineers, and analytics professionals and for anyone who works with data. You'll be able to: Gain the necessary knowledge of different data science techniques to extract value from data. Master the concepts and inner workings of 30 commonly used powerful data science algorithms. Implement step-by-step data science process using using RapidMiner, an open source GUI based data science platform Data Science techniques covered: Exploratory data analysis, Visualization, Decision trees, Rule induction, k-nearest neighbors, Naive Bayesian classifiers, Artificial neural networks, Deep learning, Support vector machines, Ensemble models, Random forests, Regression, Recommendation engines, Association analysis, K-Means and Density based clustering, Self organizing maps, Text mining, Time series forecasting, Anomaly detection, Feature selection and more...

Social Network Analytics: Computational Research Methods and Techniques focuses on various technical concepts and aspects of social network analysis. The book features the latest developments and findings in this emerging area of research. In addition, it includes a variety of applications from several domains, such as scientific research, and the business and industrial sectors. The technical aspects of analysis are covered in detail, including visualizing and modeling, network theory, mathematical models, the big data analytics of social networks, multidimensional scaling, and more. As analyzing social network data is rapidly gaining interest in the scientific research community because of the importance of the information and insights that can be culled from the wealth of data inherent in the various aspects of the network, this book provides insights on measuring the relationships and flows between people, groups, organizations, computers, URLs, and more.

This is a glossary of over 2,000 terms which provides a common data management vocabulary for IT and Business professionals, and is a companion to the "DAMA Data Management Body of Knowledge (DAMA-DMBOK)". Topics include: Analytics & Data Mining; Architecture; Artificial Intelligence; Business Analysis; DAMA & Professional Development; Databases & Database Design; Database Administration; Data Governance & Stewardship; Data Management; Data Modeling; Data Movement & Integration; Data Quality Management; Data Security Management; Data Warehousing & Business Intelligence; Document, Record & Content Management; Finance & Accounting; Geospatial Data; Knowledge Management; Marketing & Customer Relationship Management; Meta-Data Management; Multi-dimensional & OLAP; Normalization; Object-Orientation; Parallel Database Processing; Planning; Process Management; Project Management; Reference & Master Data Management; Semantic Modeling; Software Development; Standards Organizations; Structured Query Language (SQL); and, XML Development.