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Data-Driven Decision Making

by Vinod Sharma Chandan Maheshkar Jeanne Poulose

This book delves into contemporary business analytics techniques across sectors for critical decision-making. It combines data, mathematical and statistical models, and information technology to present alternatives for decision evaluation. Offering systematic mechanisms, it explores business contexts, factors, and relationships to foster competitiveness. Beyond managerial perspectives, it includes contributions from professionals, academics, and scholars worldwide, delivering comprehensive knowledge and skills through diverse viewpoints, cases, and applications of analytical tools. As an international business science reference, it targets professionals, academics, researchers, doctoral scholars, postgraduate students, and research organizations seeking a nuanced understanding of modern business analytics.

Data-Driven Decision Making for Product Service Systems

by Xavier Boucher Giuditta Pezzotta Roberto Sala Marco Bertoni Fabiana Pirola

This book is a compilation of theoretical and practical contributions aimed at facilitating the servitization of manufacturing companies, specifically focusing on data-driven decision-making within the context of Product-Service Systems (PSS). Providing a comprehensive overview, it discusses the latest breakthroughs in operational, tactical, and strategic decision-making for PSS, leveraging data-driven processes, methodologies, and tools. Therefore, the book significantly contributes to strengthening the knowledge on the use of data-driven decision-making methods and tools all the phases of the PSS lifecycle.From extended warranties and leasing to pay-per-use and other innovative configurations, manufacturing companies are increasingly adopting servitized business models and PSS to create additional value for their customers and users and create robust relationships with them, ensuring more reliable cash flows. In this setting, effective information management and the utilization of aggregated operational data have become essential for guiding strategic, tactical, and operational decisions.This book not only consolidates theoretical frameworks but also offers practical insights into data-driven decision-making in PSS, providing deep knowledge on how complex decisions can be taken along the various phases of the PSS lifecycle using data-driven methods and tools. Key areas of focus include: 1. In the Beginning of Life, introducing new services tailored to customer needs, disclosing new business opportunities in terms of revenues, and extending the PSS Middle of Life.2. Designing or re-designing assets and/or services, thereby influencing the PSS Beginning of Life.3. Enhancing daily decisions related to asset management to improve the PSS Middle of Life.4. Optimizing daily decisions related to service delivery and management, aimed at enhancing the PSS Middle of Life.5. Facilitating informed decisions on recycling, remanufacturing, refurbishing, and revamping, impacting the PSS End of Life.This book will be of interest to researchers and managers in industry as it offers insights that bridge the gap between theory and practical application in the evolving landscape of PSS.

Data-Driven Decision Making im operativen und strategischen Investitionscontrolling: Entwicklung eines prozessorientierten Ansatzes (essentials)

by Jessica Hastenteufel Luca Weigerding

Dieses Essential bietet eine praxisnahe Einführung in datengetriebene Entscheidungsprozesse und deren Anwendung im Investitionscontrolling. Es erklärt theoretische Grundlagen und zeigt, wie Big Data und moderne Analysemethoden traditionelle Ansätze revolutionieren. Anhand von Beispielen und Handlungsempfehlungen wird veranschaulicht, wie Unternehmen durch datenbasierte Entscheidungen Wettbewerbsvorteile erzielen können. Besonders im Fokus stehen die Optimierung von Prozessen, die Risikominimierung und die effektive Nutzung moderner Technologien wie Machine Learning und Datenvisualisierung. Dieses Werk ist ein unverzichtbarer Leitfaden für Entscheider und Controller, die datengetriebene Strategien umsetzen möchten.

Data-Driven Decision Making in Entrepreneurship: Tools for Maximizing Human Capital

by Nikki Blacksmith Maureen E. McCusker

Since the beginning of the 21st century, there has been an explosion in startup organizations. Together, these organizations have been valued at over $3 trillion. In 2019, alone, nearly $300 billion of venture capital was invested globally (Global Startup Ecosystem Report 2020). Simultaneously, an explosion in high volume and high velocity of big data is rapidly changing how organizations function. Gone are the days where organizations can make decisions solely on intuition, logic, or experience. Some have gone as far as to say that data is the most valuable currency and resource available to businesses, and startups are no exception. However, startups and small businesses do differ from their larger counterparts and corporations in three distinct ways: 1) they tend to have fewer resources, time, and specialized training to devote to data analytics; 2) they are part of a unique entrepreneurial ecosystem with unique needs; 3) scholarship and academic research on human capital data analytics in startups is lacking. Existing entrepreneurship research focuses almost exclusively on macro-level aspects. There has been little to no integration of micro- and meso-level research (i.e., individual and team sciences), which is unfortunate given how organizational scientists have significantly advanced human capital data analytics. Unlike other books focused on data analytics and decision for organizations, this proposed book is purposefully designed to be more specifically aimed at addressing the unique idiosyncrasies of the science, research, and practice of startups. Each chapter highlights a specific organizational domain and discuss how a novel data analytic technique can help enhance decision-making, provides a tutorial of said regarding the data analytic technique, and lists references and resources for the respective data analytic technique. The volume will be grounded in sound theory and practice of organizational psychology, entrepreneurship and management and is divided into two parts: assessing and evaluating human capital performance and the use of data analytics to manage human capital.

Data-Driven Decision-Making for Business

by Claus Grand Bang

Research shows that companies that employ data-driven decision-making are more productive, have a higher market value, and deliver higher returns for their shareholders. In this book, the reader will discover the history, theory, and practice of data-driven decision-making, learning how organizations and individual managers alike can utilize its methods to avoid cognitive biases and improve confidence in their decisions. It argues that value does not come from data, but from acting on data.Throughout the book, the reader will examine how to convert data to value through data-driven decision-making, as well as how to create a strong foundation for such decision-making within organizations. Covering topics such as strategy, culture, analysis, and ethics, the text uses a collection of diverse and up-to-date case studies to convey insights which can be developed into future action. Simultaneously, the text works to bridge the gap between data specialists and businesspeople. Clear learning outcomes and chapter summaries ensure that key points are highlighted, enabling lecturers to easily align the text to their curriculums.Data-Driven Decision-Making for Business provides important reading for undergraduate and postgraduate students of business and data analytics programs, as well as wider MBA classes. Chapters can also be used on a standalone basis, turning the book into a key reference work for students graduating into practitioners. The book is supported by online resources, including PowerPoint slides for each chapter.

Data-Driven Design and Construction

by Randy Deutsch

"In this comprehensive book, Professor Randy Deutsch has unlocked and laid bare the twenty-first century codice nascosto of architecture. It is data. Big data. Data as driver. . . This book offers us the chance to become informed and knowledgeable pursuers of data and the opportunities it offers to making architecture a wonderful, useful, and smart art form. " --From the Foreword by James Timberlake, FAIA Written for architects, engineers, contractors, owners, and educators, and based on today's technology and practices, Data-Driven Design and Construction: 25 Strategies for Capturing, Applying and Analyzing Building Data addresses how innovative individuals and firms are using data to remain competitive while advancing their practices. seeks to address and rectify a gap in our learning, by explaining to architects, engineers, contractors and owners--and students of these fields--how to acquire and use data to make more informed decisions. documents how data-driven design is the new frontier of the convergence between BIM and architectural computational analyses and associated tools. is a book of adaptable strategies you and your organization can apply today to make the most of the data you have at your fingertips. Data-Driven Design and Construction was written to help design practitioners and their project teams make better use of BIM, and leverage data throughout the building lifecycle.

Data-Driven HR: How to Use AI, Analytics and Data to Drive Performance

by Bernard Marr

How can HR professionals utilize and leverage their organization's data effectively, with the use of AI, for more talent attraction, better employee engagement and higher talent retention to ultimately drive performance?AI is now an integral part of being data-driven. With this updated edition of Data-Driven HR, practitioners can unlock business potential and success through data and analytics. Covering topics such as recruitment, employee engagement, performance management, wellbeing and training, HR practitioners can benefit from knowing how to really be data-driven through the use of data and AI. HR teams will learn how to identify business goals, scrutinize useful sources of data and gain rich and diverse insights from their vast amounts of data. This book brings guidance on how to manage challenges that come with data and AI, as well as how to responsibly and transparently use data to improve decision making. It also includes predictive analytics and how to place warning systems into databases for any potential workforce issues. Packed with practical advice, key takeaways and real-life examples, this is essential reading for all HR professionals looking to make a measurable difference in their organizations.

Data-Driven HR: How to Use Analytics and Metrics to Drive Performance

by Bernard Marr

Traditionally seen as a purely people function unconcerned with numbers, HR is now uniquely placed to use company data to drive performance, both of the people in the organization and the organization as a whole. Data-Driven HR is a practical guide which enables HR professionals to leverage the value of the vast amount of data available at their fingertips. Covering how to identify the most useful sources of data, collect information in a transparent way that is in line with data protection requirements and turn this data into tangible insights, this book marks a turning point for the HR profession. Covering all the key elements of HR including recruitment, employee engagement, performance management, wellbeing and training, Data-Driven HR examines the ways data can contribute to organizational success by, among other things, optimizing processes, driving performance and improving HR decision making. Packed with case studies and real-life examples, this is essential reading for all HR professionals looking to make a measurable difference in their organizations.

Data-Driven Healthcare: How Analytics and BI are Transforming the Industry (Wiley and SAS Business Series)

by Laura B. Madsen

Healthcare is changing, and data is the catalyst Data is taking over in a powerful way, and it's revolutionizing the healthcare industry. You have more data available than ever before, and applying the right analytics can spur growth. Benefits extend to patients, providers, and board members, and the technology can make centralized patient management a reality. Despite the potential for growth, many in the industry and government are questioning the value of data in health care, wondering if it's worth the investment. Data-Driven Healthcare: How Analytics and BI are Transforming the Industry tackles the issue and proves why BI is not only worth it, but necessary for industry advancement. Healthcare BI guru Laura Madsen challenges the notion that data have little value in healthcare, and shows how BI can ease regulatory reporting pressures and streamline the entire system as it evolves. Madsen illustrates how a data-driven organization is created, and how it can transform the industry. Learn why BI is a boon to providers Create powerful infographics to communicate data more effectively Find out how Big Data has transformed other industries, and how it applies to healthcare Data-Driven Healthcare: How Analytics and BI are Transforming the Industry provides tables, checklists, and forms that allow you to take immediate action in implementing BI in your organization. You can't afford to be behind the curve. The industry is moving on, with or without you. Data-Driven Healthcare: How Analytics and BI are Transforming the Industry is your guide to utilizing data to advance your operation in an industry where data-fueled growth will be the new norm.

Data-Driven Innovation in the Creative Industries (Routledge Research in the Creative and Cultural Industries)

by Melissa Terras Chris Speed Vikki Jones Nicola Osborne

The creative industries – the place where art, business, and technology meet in economic activity – have been hugely affected by the relatively recent digitalisation (and often monetisation) of work, home, relationships, and leisure. Such trends were accelerated by the global COVID-19 pandemic. This edited collection examines how the creative industries can be supported to make best use of opportunities in digital technology and data-driven innovation.Since digital markets and platforms are now essential for revenue generation and audience engagement, there is a vital need for improved data and digital skills in the creative and cultural sectors. Taking a necessarily global perspective, this book explores the challenges and opportunities of data-driven approaches to creativity in different contexts across the arts, cultural, and heritage sectors. Chapters reach beyond the platforms and approaches provided by the technology sector to delve into the collaborative work that supports innovation around the interdisciplinary and cross-sectoral issues that emerge where data infrastructures and approaches meet creativity.A novel intervention that uniquely centres the role of data in the theory and practice of creative industries’ innovation, this book is valuable reading for those researching and studying the creative economy as well for those who drive investment for the creative industries in a digitalised society.The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 International license.

Data-Driven Innovation: Why the Data-Driven Model Will Be Key to Future Success

by Torben Pedersen Michael Moesgaard Andersen

Today, innovation does not just occur in large and incumbent R&D organizations. Instead, it often emerges from the start-up community. In the new innovation economy, the key is to quickly find pieces of innovation, some of which may already be developed. Therefore, there is the need for more advanced means of searching and identifying innovation wherever it may occurs. We point to the importance of data-driven innovation based on digital platforms, as their footprints are growing rapidly and in sync with the shift from analogue to digital innovation workflows. This book offers companies insights on paths to business success and tools that will help them find the right route through the various options when it comes to the digital platforms where innovations may be discovered and from which value may be appropriated. The world hungers for growth and one of the most important vehicles for growth is innovation. In light of the new digital platforms from which data-driven innovation can be extracted, major parts of analogue workflows will be substituted with digital workflows. Data-driven innovation and digital innovation workflows are here to stay. Are you?

Data-Driven Marketing und der Erfolgsfaktor Mensch: Schlüsselfaktoren und Kernkompetenzen für das Marketing der Zukunft

by Lutz Klaus

Daten, Daten, Daten – und was ist mit Menschen? Bei der Digitalisierung von Prozessen und Geschäftsmodellen werden datengetriebene Ansätze und Technologien immer bedeutender. Doch der entscheidende Faktor für den Geschäftserfolg ist der Mensch, der die Daten nutzt und Prozesse mit Leben füllt. Dieses kompakte Buch richtet sich an Marketingprofis, Verantwortliche für Digitalisierung, Personalleiter sowie an alle, die datengetriebene, analytische Ansätze als Erfolgsvoraussetzung sehen und die Zukunft in der digitalen Arbeitswelt verantwortlich gestalten wollen. Der Autor stellt einen Bezugsrahmen mit sieben Punkten vor, mit dem es gelingt, sich und andere auf die Zukunft in der von Technologie geprägten Welt vorzubereiten. Anhand konkreter Beispiele wird deutlich, warum analytisches Denken, Neugier und Integration zentrale Fähigkeiten im Marketing sind und an welchen Stellen die Agilität gesteigert werden muss. Der Leser profitiert von anwendbarem Wissen, handfesten Tipps und Hinweisen zur Umsetzung in der Praxis.

Data-Driven Marketing: The 15 Metrics Everyone In Marketing Should Know

by Mark Jeffery

NAMED BEST MARKETING BOOK OF 2011 BY THE AMERICAN MARKETING ASSOCIATIONHow organizations can deliver significant performance gains through strategic investment in marketingIn the new era of tight marketing budgets, no organization can continue to spend on marketing without knowing what's working and what's wasted. Data-driven marketing improves efficiency and effectiveness of marketing expenditures across the spectrum of marketing activities from branding and awareness, trail and loyalty, to new product launch and Internet marketing. Based on new research from the Kellogg School of Management, this book is a clear and convincing guide to using a more rigorous, data-driven strategic approach to deliver significant performance gains from your marketing.Explains how to use data-driven marketing to deliver return on marketing investment (ROMI) in any organizationIn-depth discussion of the fifteen key metrics every marketer should knowBased on original research from America's leading marketing business school, complemented by experience teaching ROMI to executives at Microsoft, DuPont, Nisan, Philips, Sony and many other firmsUses data from a rigorous survey on strategic marketing performance management of 252 Fortune 1000 firms, capturing $53 billion of annual marketing spendingIn-depth examples of how to apply the principles in small and large organizationsFree downloadable ROMI templates for all examples given in the bookWith every department under the microscope looking for results, those who properly use data to optimize their marketing are going to come out on top every time.

Data-Driven Organization Design: Delivering Perpetual Performance Gains Through the Organizational System

by Rupert Morrison

Understand how to drive business performance with your organizational data and analytics in the second edition of Data-Driven Organization Design.Using data and analytics is a key opportunity for businesses to transform performance and achieve success. With a data-driven approach, all the elements of the organizational system can be connected to design an environment in which people can excel and attain competitive advantage. Data-Driven Organization Design provides a practical framework for HR and organization design practitioners to build a baseline of data, set objectives, carry out fixed and dynamic process design, map competencies, and right-size the organization. It shows how to collect the right data, present it meaningfully and ask the most relevant questions of it to help complex, fluid organizations constantly evolve and meet moving objectives. This updated second edition contains new material on organizational planning and analysis, role design and job architecture, position management lifecycle and delta reporting. Alongside this, new case studies and examples will show how these approaches have been applied in practice. Whether planning a long-term transformation, a large redesign or an individual small project, Data-Driven Organization Design will demonstrate how to make the most of your organizational data and analytics to drive business performance.

Data-Driven Personalization: How to Use Consumer Insights to Generate Customer Loyalty

by Zontee Hou

Make your marketing truly resonate by personalizing every message, powered by data, research and behavioral economics. To break through the noise, marketers today need to be hyper-relevant to their customers. To do that takes data and a deep understanding of your audience. Data-Driven Personalization breaks down the best ways to reach new customers and better engage your best customers. By combining principles of persuasion, behavioral economics and industry research, this book provides readers with an actionable blueprint for how to implement a customer-centric approach to marketing that will drive results. The book is broken into six parts that detail everything from what data is most valuable for personalization to how to build a data-driven marketing team that's prepared for the next five years and beyond. Each chapter includes actionable insights to guide marketers as they implement a data-driven personalization approach to their strategy. The chapters also focus on hands-on tactics like identifying messages that will move the needle with customers, how to generate seamless omnichannel experiences and how to balance personalization with data privacy. The book features case studies from top brands, including FreshDirect, Target, Adobe, Cisco and Spotify.

Data-Driven Policy Impact Evaluation: How Access to Microdata is Transforming Policy Design

by Nuno Crato Paolo Paruolo

In the light of better and more detailed administrative databases, this open access book provides statistical tools for evaluating the effects of public policies advocated by governments and public institutions. Experts from academia, national statistics offices and various research centers present modern econometric methods for an efficient data-driven policy evaluation and monitoring, assess the causal effects of policy measures and report on best practices of successful data management and usage. Topics include data confidentiality, data linkage, and national practices in policy areas such as public health, education and employment. It offers scholars as well as practitioners from public administrations, consultancy firms and nongovernmental organizations insights into counterfactual impact evaluation methods and the potential of data-based policy and program evaluation.

Data-Driven Prediction for Industrial Processes and Their Applications (Information Fusion and Data Science)

by Wei Wang Jun Zhao Chunyang Sheng

This book presents modeling methods and algorithms for data-driven prediction and forecasting of practical industrial process by employing machine learning and statistics methodologies. Related case studies, especially on energy systems in the steel industry are also addressed and analyzed. The case studies in this volume are entirely rooted in both classical data-driven prediction problems and industrial practice requirements. Detailed figures and tables demonstrate the effectiveness and generalization of the methods addressed, and the classifications of the addressed prediction problems come from practical industrial demands, rather than from academic categories. As such, readers will learn the corresponding approaches for resolving their industrial technical problems. Although the contents of this book and its case studies come from the steel industry, these techniques can be also used for other process industries. This book appeals to students, researchers, and professionals within the machine learning and data analysis and mining communities.

Data-Driven Process Discovery and Analysis: 7th IFIP WG 2.6 International Symposium, SIMPDA 2017, Neuchatel, Switzerland, December 6-8, 2017, Revised Selected Papers (Lecture Notes in Business Information Processing #340)

by Paolo Ceravolo Kilian Stoffel Maurice Van Keulen

This book constitutes the revised selected papers from the 7th IFIP WG 2.6 International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2017, held in Neuchatel, Switzerland, in December 2017. The 6 papers presented in this volume were carefully reviewed and selected from 19 submissions. They cover theoretical issues related to process representation, discovery, and analysis or provide practical and operational examples of their application.

Data-Driven Process Discovery and Analysis: 8th IFIP WG 2.6 International Symposium, SIMPDA 2018, Seville, Spain, December 13–14, 2018, and 9th International Symposium, SIMPDA 2019, Bled, Slovenia, September 8, 2019, Revised Selected Papers (Lecture Notes in Business Information Processing #379)

by Paolo Ceravolo Maurice Van Keulen María Teresa Gómez-López

This book constitutes revised selected papers from the 8th and 9th IFIP WG 2.6 International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2018, held in Seville, Spain, on December 13–14, 2018, and SIMPDA 2019, held in Bled, Slovenia, on September 8, 2019. From 16 submissions received for SIMPDA 2018 and 9 submissions received for SIMPDA 2019, 3 papers each were carefully reviewed and selected for presentation in this volume. They cover theoretical issues related to process representation, discovery, and analysis or provide practical and operational examples of their application.

Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications (Springer Series in Reliability Engineering)

by Xiao-Sheng Si Zheng-Xin Zhang Chang-Hua Hu

This book introduces data-driven remaining useful life prognosis techniques, and shows how to utilize the condition monitoring data to predict the remaining useful life of stochastic degrading systems and to schedule maintenance and logistics plans. It is also the first book that describes the basic data-driven remaining useful life prognosis theory systematically and in detail. The emphasis of the book is on the stochastic models, methods and applications employed in remaining useful life prognosis. It includes a wealth of degradation monitoring experiment data, practical prognosis methods for remaining useful life in various cases, and a series of applications incorporated into prognostic information in decision-making, such as maintenance-related decisions and ordering spare parts. It also highlights the latest advances in data-driven remaining useful life prognosis techniques, especially in the contexts of adaptive prognosis for linear stochastic degrading systems, nonlinear degradation modeling based prognosis, residual storage life prognosis, and prognostic information-based decision-making.

Data-Driven Smart Community Design: Strategies for Fostering Inclusive and Resilient Neighbourhoods

by Keng Hua Chong

This book couples data analytics with social behavioural studies and participatory design to derive deeper insights on city dwellers’ present needs and future aspirations, thereby enabling the development of targeted spatial and programmatic interventions for diverse communities.Public housing in Singapore has been regarded internationally as a success story. This book outlines the latest strategies and concepts for addressing the emerging social challenges of the ageing population: shrinking household size, increasingly diverse demographics and widening inequality, and fostering inclusive and resilient neighbourhoods. Adopting an interdisciplinary approach, this book: Outlines an innovative data-driven planning process for housing neighbourhood and community design Provides a framework for planners and designers to synthesise qualitative and quantitative data analyses Presents a comprehensive set of tested urban analytics tools, digital platforms and participatory toolkits used to design and develop community initiatives. A recommended text for students undertaking urban planning, urban design, housing design, architecture, real estate, urban sociology and community design, the book’s strategies for evidence-based neighbourhood designs will also appeal to practitioners and policymakers.The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons [Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND)] 4.0 license.

Data-Enabled Analytics: DEA for Big Data (International Series in Operations Research & Management Science #312)

by Joe Zhu Vincent Charles

This book explores the novel uses and potentials of Data Envelopment Analysis (DEA) under big data. These areas are of widespread interest to researchers and practitioners alike. Considering the vast literature on DEA, one could say that DEA has been and continues to be, a widely used technique both in performance and productivity measurement, having covered a plethora of challenges and debates within the modelling framework.

Data-First Marketing: How To Compete and Win In the Age of Analytics

by Janet Driscoll Miller Julia Lim

Supercharge your marketing strategy with data analytics In Data-First Marketing: How to Compete & Win in the Age of Analytics, distinguished authors Miller and Lim demystify the application of data analytics to marketing in any size business. Digital transformation has created a widening gap between what the CEO and business expect marketing to do and what the CMO and the marketing organization actually deliver. The key to unlocking the true value of marketing is data – from actual buyer behavior to targeting info on social media platforms to marketing’s own campaign metrics. Data is the next big battlefield for not just marketers, but also for the business because the judicious application of data analytics will create competitive advantage in the Age of Analytics. Miller and Lim show marketers where to start by leveraging their decades of experience to lay out a step-by-step process to help businesses transform into data-first marketing organizations. The book includes a self-assessment which will help to place your organization on the Data-First Marketing Maturity Model and serve as a guide for which steps you might need to focus on to complete your own transformation. Data-First Marketing: How to Compete & Win in the Age of Analytics should be used by CMOs and heads of marketing to institute a data-first approach throughout the marketing organization. Marketing staffers can pick up practical tips for incorporating data in their daily tasks using the Data-First Marketing Campaign Framework. And CEOs or anyone in the C-suite can use this book to see what is possible and then help their marketing teams to use data analytics to increase pipeline, revenue, customer loyalty – anything that drives business growth.

Data-Intensive Science (Chapman And Hall/crc Computational Science Ser. #18)

by Terence Critchlow Kerstin Kleese Van Dam

Data-intensive science has the potential to transform scientific research and quickly translate scientific progress into complete solutions, policies, and economic success. But this collaborative science is still lacking the effective access and exchange of knowledge among scientists, researchers, and policy makers across a range of disciplines. Bringing together leaders from multiple scientific disciplines, Data-Intensive Science shows how a comprehensive integration of various techniques and technological advances can effectively harness the vast amount of data being generated and significantly accelerate scientific progress to address some of the world's most challenging problems. In the book, a diverse cross-section of application, computer, and data scientists explores the impact of data-intensive science on current research and describes emerging technologies that will enable future scientific breakthroughs. The book identifies best practices used to tackle challenges facing data-intensive science as well as gaps in these approaches. It also focuses on the integration of data-intensive science into standard research practice, explaining how components in the data-intensive science environment need to work together to provide the necessary infrastructure for community-scale scientific collaborations. Organizing the material based on a high-level, data-intensive science workflow, this book provides an understanding of the scientific problems that would benefit from collaborative research, the current capabilities of data-intensive science, and the solutions to enable the next round of scientific advancements.

Data-Warehouse-Systeme kompakt: Aufbau, Architektur, Grundfunktionen (Xpert.press)

by Kiumars Farkisch

In dem Buch werden Data-Warehouse-Systeme als einheitliche, zentrale, vollständige, historisierte und analytische IT-Plattform untersucht und ihre Rolle für die Datenanalyse und für Entscheidungsfindungsprozesse dargestellt. Dabei behandelt der Autor die einzelnen Komponenten, die für den Aufbau, die Architektur und den Betrieb eines Data-Warehouse-Systems von Bedeutung sind. Die multidimensionale Datenmodellierung, der ETL-Prozess und Analysemethoden werden erörtert und Maßnahmen zur Performancesteigerung von Data-Warehouse-Systemen diskutiert.

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