Gartner Data Science Quadrant

  gartner data science quadrant: Applied Data Science Martin Braschler, Thilo Stadelmann, Kurt Stockinger, 2019-06-13 This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at the intersection of academia and industry. As such, it is not a replacement for a classical textbook (i.e., it does not elaborate on fundamentals of methods and principles described elsewhere), but systematically highlights the connection between theory, on the one hand, and its application in specific use cases, on the other. With these goals in mind, the book is divided into three parts: Part I pays tribute to the interdisciplinary nature of data science and provides a common understanding of data science terminology for readers with different backgrounds. These six chapters are geared towards drawing a consistent picture of data science and were predominantly written by the editors themselves. Part II then broadens the spectrum by presenting views and insights from diverse authors – some from academia and some from industry, ranging from financial to health and from manufacturing to e-commerce. Each of these chapters describes a fundamental principle, method or tool in data science by analyzing specific use cases and drawing concrete conclusions from them. The case studies presented, and the methods and tools applied, represent the nuts and bolts of data science. Finally, Part III was again written from the perspective of the editors and summarizes the lessons learned that have been distilled from the case studies in Part II. The section can be viewed as a meta-study on data science across a broad range of domains, viewpoints and fields. Moreover, it provides answers to the question of what the mission-critical factors for success in different data science undertakings are. The book targets professionals as well as students of data science: first, practicing data scientists in industry and academia who want to broaden their scope and expand their knowledge by drawing on the authors’ combined experience. Second, decision makers in businesses who face the challenge of creating or implementing a data-driven strategy and who want to learn from success stories spanning a range of industries. Third, students of data science who want to understand both the theoretical and practical aspects of data science, vetted by real-world case studies at the intersection of academia and industry.
  gartner data science quadrant: Data Science, Data Visualization, and Digital Twins Sara Shirowzhan, 2022-02-02 Real-time, web-based, and interactive visualisations are proven to be outstanding methodologies and tools in numerous fields when knowledge in sophisticated data science and visualisation techniques is available. The rationale for this is because modern data science analytical approaches like machine/deep learning or artificial intelligence, as well as digital twinning, promise to give data insights, enable informed decision-making, and facilitate rich interactions among stakeholders.The benefits of data visualisation, data science, and digital twinning technologies motivate this book, which exhibits and presents numerous developed and advanced data science and visualisation approaches. Chapters cover such topics as deep learning techniques, web and dashboard-based visualisations during the COVID pandemic, 3D modelling of trees for mobile communications, digital twinning in the mining industry, data science libraries, and potential areas of future data science development.
  gartner data science quadrant: Data Science & Business Analytics Sneha Kumari, K. K. Tripathy, Vidya Kumbhar, 2020-12-04 Data Science & Business Analytics explores the application of big data and business analytics by academics, researchers, industrial experts, policy makers and practitioners, helping the reader to understand how big data can be efficiently utilized in better managerial applications.
  gartner data science quadrant: Real Business of IT Richard Hunter, George Westerman, 2009-10-20 If you're a general manager or CFO, do you feel you're spending too much on IT or wishing you could get better returns from your IT investments? If so, it's time to examine what's behind this IT-as-cost mind-set. In The Real Business of IT, Richard Hunter and George Westerman reveal that the cost mind-set stems from IT leaders' inability to communicate about the business value they create-so CIOs get stuck discussing budgets rather than their contributions to the organization. The authors explain how IT leaders can combat this mind-set by first using information technology to generate three forms of value important to leaders throughout the organization: -Value for money when your IT department operates efficiently and effectively -An investment in business performance evidenced when IT helps divisions, units, and departments boost profitability -Personal value of CIOs as leaders whose contributions to their enterprise go well beyond their area of specialization The authors show how to communicate about these forms of value with non-IT leaders-so they understand how your firm is benefiting and see IT as the strategic powerhouse it truly is.
  gartner data science quadrant: Harnessing the Power of Analytics Leila Halawi, Amal Clarke, Kelly George, 2022-01-31 This text highlights the difference between analytics and data science, using predictive analytic techniques to analyze different historical data, including aviation data and concrete data, interpreting the predictive models, and highlighting the steps to deploy the models and the steps ahead. The book combines the conceptual perspective and a hands-on approach to predictive analytics using SAS VIYA, an analytic and data management platform. The authors use SAS VIYA to focus on analytics to solve problems, highlight how analytics is applied in the airline and business environment, and compare several different modeling techniques. They decipher complex algorithms to demonstrate how they can be applied and explained within improving decisions.
  gartner data science quadrant: Information Technology for Management Efraim Turban, Carol Pollard, Gregory R. Wood, 2021 Information Technology for Management provides students with a comprehensive understanding of the latest technological developments in IT and the critical drivers of business performance, growth, and sustainability. Integrating feedback from IT managers and practitioners from top-level organizations worldwide, the International Adaptation of this well-regarded textbook features thoroughly revised content throughout to present students with a realistic, up-to-date view of IT management in the current business environment. This text covers the latest developments in the real world of IT management with the addition of new case studies that are contemporary and more relevant to the global scenario. It offers a flexible, student-friendly presentation of the material through a pedagogy that is designed to help students easily comprehend and retain information. There is new and expanded coverage of Artificial Intelligence, Robotics, Quantum Computing, Blockchain Technology, IP Intelligence, Big Data Analytics, IT Service Management, DevOps, etc. It helps readers learn how IT is leveraged to reshape enterprises, engage and retain customers, optimize systems and processes, manage business relationships and projects, and more.
  gartner data science quadrant: R for Stata Users Robert A. Muenchen, Joseph M. Hilbe, 2010-04-26 Stata is the most flexible and extensible data analysis package available from a commercial vendor. R is a similarly flexible free and open source package for data analysis, with over 3,000 add-on packages available. This book shows you how to extend the power of Stata through the use of R. It introduces R using Stata terminology with which you are already familiar. It steps through more than 30 programs written in both languages, comparing and contrasting the two packages' different approaches. When finished, you will be able to use R in conjunction with Stata, or separately, to import data, manage and transform it, create publication quality graphics, and perform basic statistical analyses. A glossary defines over 50 R terms using Stata jargon and again using more formal R terminology. The table of contents and index allow you to find equivalent R functions by looking up Stata commands and vice versa. The example programs and practice datasets for both R and Stata are available for download.
  gartner data science quadrant: Social Big Data Analytics Bilal Abu-Salih, Pornpit Wongthongtham, Dengya Zhu, Kit Yan Chan, Amit Rudra, 2021-03-10 This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising. This book identifies how in such applications, social data offers a plethora of benefits to enhance the decision making process. This book highlights that business intelligence applications are more focused on structured data; however, in order to understand and analyse the social big data, there is a need to aggregate data from various sources and to present it in a plausible format. Big Social Data (BSD) exhibit all the typical properties of big data: wide physical distribution, diversity of formats, non-standard data models, independently-managed and heterogeneous semantics but even further valuable with marketing opportunities. The book provides a review of the current state-of-the-art approaches for big social data analytics as well as to present dissimilar methods to infer value from social data. The book further examines several areas of research that benefits from the propagation of the social data. In particular, the book presents various technical approaches that produce data analytics capable of handling big data features and effective in filtering out unsolicited data and inferring a value. These approaches comprise advanced technical solutions able to capture huge amounts of generated data, scrutinise the collected data to eliminate unwanted data, measure the quality of the inferred data, and transform the amended data for further data analysis. Furthermore, the book presents solutions to derive knowledge and sentiments from BSD and to provide social data classification and prediction. The approaches in this book also incorporate several technologies such as semantic discovery, sentiment analysis, affective computing and machine learning. This book has additional special feature enriched with numerous illustrations such as tables, graphs and charts incorporating advanced visualisation tools in accessible an attractive display.
  gartner data science quadrant: Data Science with Applied Statistics in Python Dr.A Manimaran, Dr.A.Selvakumar, Dr.S. Ramesh, Dr.J.Chenni Kumaran, Dr.M.Sivaram, 2024-02-05 Dr.A Manimaran, Profesor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India. Dr.A.Selvakumar, Profesor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India. Dr.S. Ramesh, Profesor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India. Dr.J.Chenni Kumaran, Professor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India. Dr.M.Sivaram, Profesor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India.
  gartner data science quadrant: R for SAS and SPSS Users Robert A. Muenchen, 2011-08-27 R is a powerful and free software system for data analysis and graphics, with over 5,000 add-on packages available. This book introduces R using SAS and SPSS terms with which you are already familiar. It demonstrates which of the add-on packages are most like SAS and SPSS and compares them to R's built-in functions. It steps through over 30 programs written in all three packages, comparing and contrasting the packages' differing approaches. The programs and practice datasets are available for download. The glossary defines over 50 R terms using SAS/SPSS jargon and again using R jargon. The table of contents and the index allow you to find equivalent R functions by looking up both SAS statements and SPSS commands. When finished, you will be able to import data, manage and transform it, create publication quality graphics, and perform basic statistical analyses. This new edition has updated programming, an expanded index, and even more statistical methods covered in over 25 new sections.
  gartner data science quadrant: Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry Chkoniya, Valentina, 2021-06-25 The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.
  gartner data science quadrant: Machine Learning for Cyber Physical Systems Jürgen Beyerer, Christian Kühnert, Oliver Niggemann, 2018-12-17 This Open Access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, October 23-24, 2018. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.
  gartner data science quadrant: Data Science and Analytics Strategy Kailash Awati, Alexander Scriven, 2023-04-05 This book describes how to establish data science and analytics capabilities in organisations using Emergent Design, an evolutionary approach that increases the chances of successful outcomes while minimising upfront investment. Based on their experiences and those of a number of data leaders, the authors provide actionable advice on data technologies, processes, and governance structures so that readers can make choices that are appropriate to their organisational contexts and requirements. The book blends academic research on organisational change and data science processes with real-world stories from experienced data analytics leaders, focusing on the practical aspects of setting up a data capability. In addition to a detailed coverage of capability, culture, and technology choices, a unique feature of the book is its treatment of emerging issues such as data ethics and algorithmic fairness. Data Science and Analytics Strategy: An Emergent Design Approach has been written for professionals who are looking to build data science and analytics capabilities within their organisations as well as those who wish to expand their knowledge and advance their careers in the data space. Providing deep insights into the intersection between data science and business, this guide will help professionals understand how to help their organisations reap the benefits offered by data. Most importantly, readers will learn how to build a fit-for-purpose data science capability in a manner that avoids the most common pitfalls.
  gartner data science quadrant: Gartner and the Magic Quadrant Shaun Snapp, 2013-10 If you want to get more out of your Gartner research subscription, this book is for you! Whether you are a software buyer, a large or small vendor, or are wondering how Gartner can help you make better investment decisions, this book will give you new insights to Gartner's research. By studying the methodology behind such popular analytical tools as the Magic Quadrant, you will understand how a vendor earned its rating and whether or not the ratings are justified! Starting with the history of Gartner and how it compares to other IT analyst firms, this book gives a realistic assessment of the value of Gartner research to a company and provides ideas about other resources that could complement Gartner's analysis. You will also have the tools to level the playing field between large, medium and small vendors when using Gartner's analysis in selecting software. By reading this book, you will: Evaluate whether or not a Gartner subscription is of value to your company Adjust the Magic Quadrant to get a more realistic assessment of large and small vendors and their products Increase the value of your interactions with Gartner analysts Understand Gartner's biases and how Gartner makes money, and how this impacts its research results Appreciate the effects of cloud computing on Gartner, and why it matters to you Choose consulting services with confidence Assess the value of Gartner's other analytical products to your business
  gartner data science quadrant: Data Science for Business Professionals Probyto Data Science and Consulting Pvt. Ltd., 2020-05-06 Primer into the multidisciplinary world of Data Science KEY FEATURESÊÊ - Explore and use the key concepts of Statistics required to solve data science problems - Use Docker, Jenkins, and Git for Continuous Development and Continuous Integration of your web app - Learn how to build Data Science solutions with GCP and AWS DESCRIPTIONÊ The book will initially explain the What-Why of Data Science and the process of solving a Data Science problem. The fundamental concepts of Data Science, such as Statistics, Machine Learning, Business Intelligence, Data pipeline, and Cloud Computing, will also be discussed. All the topics will be explained with an example problem and will show how the industry approaches to solve such a problem. The book will pose questions to the learners to solve the problems and build the problem-solving aptitude and effectively learn. The book uses Mathematics wherever necessary and will show you how it is implemented using Python with the help of an example dataset.Ê WHAT WILL YOU LEARNÊÊ - Understand the multi-disciplinary nature of Data Science - Get familiar with the key concepts in Mathematics and Statistics - Explore a few key ML algorithms and their use cases - Learn how to implement the basics of Data Pipelines - Get an overview of Cloud Computing & DevOps - Learn how to create visualizations using Tableau WHO THIS BOOK IS FORÊ This book is ideal for Data Science enthusiasts who want to explore various aspects of Data Science. Useful for Academicians, Business owners, and Researchers for a quick reference on industrial practices in Data Science.Ê TABLE OF CONTENTS 1. Data Science in Practice 2. Mathematics Essentials 3. Statistics Essentials 4. Exploratory Data Analysis 5. Data preprocessing 6. Feature Engineering 7. Machine learning algorithms 8. Productionizing ML models 9. Data Flows in Enterprises 10. Introduction to Databases 11. Introduction to Big Data 12. DevOps for Data Science 13. Introduction to Cloud Computing 14. Deploy Model to Cloud 15. Introduction to Business IntelligenceÊ 16. Data Visualization Tools 17. Industry Use Case 1 Ð FormAssist 18. Industry Use Case 2 Ð PeopleReporter 19. Data Science Learning Resources 20. Do It Your Self Challenges 21. MCQs for Assessments
  gartner data science quadrant: Modern Computational Techniques for Engineering Applications Krishan Arora, Vikram Kumar, Deepak Prashar, Suman Lata Tripathi, 2023-07-21 Modern Computational Techniques for Engineering Applications presents recent computational techniques used in the advancement of modern grids with the integration of non-conventional energy sources like wind and solar energy. It covers data analytics tools for smart cities, smart towns, and smart computing for sustainable development. This book- Discusses the importance of renewable energy source applications wind turbines and solar panels for electrical grids. Presents optimization-based computing techniques like fuzzy logic, neural networks, and genetic algorithms that enhance the computational speed. Showcases cloud computing tools and methodologies such as cybersecurity testbeds and data security for better accuracy of data. Covers novel concepts on artificial neural networks, fuzzy systems, machine learning, and artificial intelligence techniques. Highlights application-based case studies including cloud computing, optimization methods, and the Industrial Internet of Things. The book comprehensively introduces modern computational techniques, starting from basic tools to highly advanced procedures, and their applications. It further highlights artificial neural networks, fuzzy systems, machine learning, and artificial intelligence techniques and how they form the basis for algorithms. It presents application-based case studies on cloud computing, optimization methods, blockchain technology, fog and edge computing, and the Industrial Internet of Things. It will be a valuable resource for senior undergraduates, graduate students, and academic researchers in diverse fields, including electrical engineering, electronics and communications engineering, and computer engineering.
  gartner data science quadrant: Building the Data Lakehouse Bill Inmon, Ranjeet Srivastava, Mary Levins, 2021-10 The data lakehouse is the next generation of the data warehouse and data lake, designed to meet today's complex and ever-changing analytics, machine learning, and data science requirements. Learn about the features and architecture of the data lakehouse, along with its powerful analytical infrastructure. Appreciate how the universal common connector blends structured, textual, analog, and IoT data. Maintain the lakehouse for future generations through Data Lakehouse Housekeeping and Data Future-proofing. Know how to incorporate the lakehouse into an existing data governance strategy. Incorporate data catalogs, data lineage tools, and open source software into your architecture to ensure your data scientists, analysts, and end users live happily ever after.
  gartner data science quadrant: Handbook of Research on Essential Information Approaches to Aiding Global Health in the One Health Context Lima de Magalhães, Jorge, Hartz, Zulmira, Jamil, George Leal, Silveira, Henrique, Jamil, Liliane C., 2021-10-22 Post COVID-19 pandemic, researchers have been evaluating the healthcare system for improvements that can be made. Understanding global healthcare systems’ operations is essential to preventative measures to be taken for the next global health crisis. A key part to bettering healthcare is the implementation of information management and One Health. The Handbook of Research on Essential Information Approaches to Aiding Global Health in the One Health Context evaluates the concepts in global health and the application of essential information management in healthcare organizational strategic contexts. This text promotes understanding in how evaluation health and information management are decisive for health planning, management, and implementation of the One Health concept. Covering topics like development partnerships, global health, and the nature of pandemics, this text is essential for health administrators, policymakers, government officials, public health officials, information systems experts, data scientists, analysts, health information science and global health scholars, researchers, practitioners, doctors, students, and academicians.
  gartner data science quadrant: Data-Driven Modelling and Predictive Analytics in Business and Finance Alex Khang, Rashmi Gujrati, Hayri Uygun, R. K. Tailor, Sanjaya Gaur, 2024-07-24 Data-driven and AI-aided applications are next-generation technologies that can be used to visualize and realize intelligent transactions in finance, banking, and business. These transactions will be enabled by powerful data-driven solutions, IoT technologies, AI-aided techniques, data analytics, and visualization tools. To implement these solutions, frameworks will be needed to support human control of intelligent computing and modern business systems. The power and consistency of data-driven competencies are a critical challenge, and so is developing explainable AI (XAI) to make data-driven transactions transparent. Data- Driven Modelling and Predictive Analytics in Business and Finance covers the need for intelligent business solutions and applications. Explaining how business applications use algorithms and models to bring out the desired results, the book covers: Data-driven modelling Predictive analytics Data analytics and visualization tools AI-aided applications Cybersecurity techniques Cloud computing IoT-enabled systems for developing smart financial systems This book was written for business analysts, financial analysts, scholars, researchers, academics, professionals, and students so they may be able to share and contribute new ideas, methodologies, technologies, approaches, models, frameworks, theories, and practices.
  gartner data science quadrant: Big Data Analysis: New Algorithms for a New Society Nathalie Japkowicz, Jerzy Stefanowski, 2015-12-16 This edited volume is devoted to Big Data Analysis from a Machine Learning standpoint as presented by some of the most eminent researchers in this area. It demonstrates that Big Data Analysis opens up new research problems which were either never considered before, or were only considered within a limited range. In addition to providing methodological discussions on the principles of mining Big Data and the difference between traditional statistical data analysis and newer computing frameworks, this book presents recently developed algorithms affecting such areas as business, financial forecasting, human mobility, the Internet of Things, information networks, bioinformatics, medical systems and life science. It explores, through a number of specific examples, how the study of Big Data Analysis has evolved and how it has started and will most likely continue to affect society. While the benefits brought upon by Big Data Analysis are underlined, the book also discusses some of the warnings that have been issued concerning the potential dangers of Big Data Analysis along with its pitfalls and challenges.
  gartner data science quadrant: Advanced Practical Approaches to Web Mining Techniques and Application Obaid, Ahmed J., Polkowski, Zdzislaw, Bhushan, Bharat, 2022-03-18 The rapid increase of web pages has introduced new challenges for many organizations as they attempt to extract information from a massive corpus of web pages. Finding relevant information, eliminating irregular content, and retrieving accurate results has become extremely difficult in today’s world where there is a surplus of information available. It is crucial to further understand and study web mining in order to discover the best ways to connect users with appropriate information in a timely manner. Advanced Practical Approaches to Web Mining Techniques and Application aims to illustrate all the concepts of web mining and fosters transformative, multidisciplinary, and novel approaches that introduce the practical method of analyzing various web data sources and extracting knowledge by taking into consideration the unique challenges present in the environment. Covering a range of topics such as data science and security threats, this reference work is ideal for industry professionals, researchers, academicians, practitioners, scholars, instructors, and students.
  gartner data science quadrant: Handbook of Research on Foundations and Applications of Intelligent Business Analytics Sun, Zhaohao, Wu, Zhiyou, 2022-03-11 Intelligent business analytics is an emerging technology that has become a mainstream market adopted broadly across industries, organizations, and geographic regions. Intelligent business analytics is a current focus for research and development across academia and industries and must be examined and considered thoroughly so businesses can apply the technology appropriately. The Handbook of Research on Foundations and Applications of Intelligent Business Analytics examines the technologies and applications of intelligent business analytics and discusses the foundations of intelligent analytics such as intelligent mining, intelligent statistical modeling, and machine learning. Covering topics such as augmented analytics and artificial intelligence systems, this major reference work is ideal for scholars, engineers, professors, practitioners, researchers, industry professionals, academicians, and students.
  gartner data science quadrant: Artificial Intelligence in Management Andrzej Wodecki, 2020-11-27 Autonomous systems are on the frontiers of Artificial Intelligence (AI) research, and they are slowly finding their business applications. Driven mostly by Reinforcement Learning (RL) methods (one of the most difficult, but also the most promising modern AI algorithms), autonomous systems help create self-learning and self-optimising systems, ranging from simple game-playing agents to robots able to efficiently act in completely new environments. Based on in-depth study of more than 100 projects, Andrzej Wodecki explores RL as a key component of modern digital technologies, its real-life applications to activities in a value chain and the ways in which it impacts different industries.
  gartner data science quadrant: Social Media for Progressive Public Relations Outi Niininen, 2022-11-10 This edited book presents a comprehensive, research-led coverage of the progressive ways public relations (PR) and social media is utilised today. It offers innovative research approaches to explore PR and social media initiatives, and in so doing, provides guidance on how to direct PR communication across the complex canvas of social media where some of the communication can be highly emotional varying from overt expressions of loyalty to brandjacking. Progressive organisations are carefully engaging with their audiences in multiple social media channels with organisational goals including commercial success, sustainability or employee morale. The analytics offered by social media channels help organisations to learn about their audiences as well as design highly personalised content. This book extends our understanding of the ways PR and social media can be utilised for communication that resonates with target audiences in varying context. Through the academic research presented, readers can also learn innovative ways to investigate and improve their own PR and social media practice. The book’s main themes include the power of engagement, progressive management use of social media channels, business influence, social-influencing for non-profit causes and political impacts of targeted social media communications. Social Media for Progressive Public Relations is for scholars, researchers and students of PR and communications. Chapters 12, 13 and 14 of this book are freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons [Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND)] 4.0 license.
  gartner data science quadrant: Experimental IR Meets Multilinguality, Multimodality, and Interaction Gareth J.F. Jones, Séamus Lawless, Julio Gonzalo, Liadh Kelly, Lorraine Goeuriot, Thomas Mandl, Linda Cappellato, Nicola Ferro, 2017-08-31 This book constitutes the refereed proceedings of the 8th International Conference of the CLEF Initiative, CLEF 2017, held in Dublin, Ireland, in September 2017. The 7 full papers and 9 short papers presented together with 6 best of the labs papers were carefully reviewed and selected from 38 submissions. In addition, this volume contains the results of 10 benchmarking labs reporting their year long activities in overview talks and lab sessions. The papers address all aspects of information access in any modality and language and cover a broad range of topics in the field of multilingual and multimodal information access evaluation.
  gartner data science quadrant: Digital Marketing Dr. K R Kumar, Dr. S. Sudhakar, Dr.G.Vani,
  gartner data science quadrant: DIGITAL MARKETING Dr. D David Winster Praveenraj, Dr. J.Ashok, Dr.K.Subramani,
  gartner data science quadrant: Marketing Management Dr.Madeswaran a,
  gartner data science quadrant: Advances in Emerging Trends and Technologies Miguel Botto-Tobar, Joffre León-Acurio, Angela Díaz Cadena, Práxedes Montiel Díaz, 2019-10-12 This book constitutes the proceedings of the 1st International Conference on Advances in Emerging Trends and Technologies (ICAETT 2019), held in Quito, Ecuador, on 29–31 May 2019, jointly organized by Universidad Tecnológica Israel, Universidad Técnica del Norte, and Instituto Tecnológico Superior Rumiñahui, and supported by SNOTRA. ICAETT 2019 brought together top researchers and practitioners working in different domains of computer science to share their expertise and to discuss future developments and potential collaborations. Presenting high-quality, peer-reviewed papers, the book discusses the following topics: Technology Trends Electronics Intelligent Systems Machine Vision Communication Security e-Learning e-Business e-Government and e-Participation
  gartner data science quadrant: Flow Rob Handfield, Phd, Tom Linton, 2022-05-30 With supply chain disruptions increasingly discussed in the media and impacting our daily lives, Flow offers an important framework and solutions for remedying the rampant delays and bottlenecks that exist in global supply chains. This book describes the concept of flow, which evokes physical properties that exist in nature, such as the flow of electricity, the flow of materials, and the flow of time. In terms of process optimization, flow encompasses the integration of end-to-end supply chains and the movement toward relocation of global supply bases to nearshore/onshore geographies. Achieving flow is essential for organizations seeking to improve their supply chain performance in a time of increasing disruption. This book highlights the high-level effectiveness of business strategies that use predictions based on the sequence of world events, global supply chains, and data by exchanged smart technologies. By broadly applying physical laws to the global supply chain, Rob Handfield and Tom Linton explore the impact of supply chain physics on global market policies, such as tariffs, factory location, pandemic response, supply base geographies, and outsourcing. The authors provide specific recommendations on what to do to improve supply chain flows, and include important insights for managers with examples from companies such as Biogen, General Motors, Siemens, and Flex with regard to their response to COVID-19. Flow is an important resource not only for procurement and supply chain management professionals, but for any manager concerned with enterprise-level success.
  gartner data science quadrant: Machine Learning and Artificial Intelligence for Agricultural Economics Chandrasekar Vuppalapati, 2021-10-04 This book discusses machine learning and artificial intelligence (AI) for agricultural economics. It is written with a view towards bringing the benefits of advanced analytics and prognostics capabilities to small scale farmers worldwide. This volume provides data science and software engineering teams with the skills and tools to fully utilize economic models to develop the software capabilities necessary for creating lifesaving applications. The book introduces essential agricultural economic concepts from the perspective of full-scale software development with the emphasis on creating niche blue ocean products. Chapters detail several agricultural economic and AI reference architectures with a focus on data integration, algorithm development, regression, prognostics model development and mathematical optimization. Upgrading traditional AI software development paradigms to function in dynamic agricultural and economic markets, this volume will be of great use to researchers and students in agricultural economics, data science, engineering, and machine learning as well as engineers and industry professionals in the public and private sectors.
  gartner data science quadrant: Applying Data Science and Learning Analytics Throughout a Learner’s Lifespan Trajkovski, Goran, Demeter, Marylee, Hayes, Heather, 2022-05-06 Research in the domains of learning analytics and educational data mining has prototyped an approach where methodologies from data science and machine learning are used to gain insights into the learning process by using large amounts of data. As many training and academic institutions are maturing in their data-driven decision making, useful, scalable, and interesting trends are emerging. Organizations can benefit from sharing information on those efforts. Applying Data Science and Learning Analytics Throughout a Learner’s Lifespan examines novel and emerging applications of data science and sister disciplines for gaining insights from data to inform interventions into learners’ journeys and interactions with academic institutions. Data is collected at various times and places throughout a learner’s lifecycle, and the learners and the institution should benefit from the insights and knowledge gained from this data. Covering topics such as learning analytics dashboards, text network analysis, and employment recruitment, this book is an indispensable resource for educators, computer scientists, faculty of higher education, government officials, educational administration, students of higher education, pre-service teachers, business professionals, researchers, and academicians.
  gartner data science quadrant: Harnessing the Power of Social Media and Web Analytics Ayanso, Anteneh, 2014-02-28 Social media has opened several new marketing channels to assist in business visibility as well as provide real-time customer feedback. With the emergence of new internet technologies, businesses are increasingly recognizing the value of social media and web presence in the promotion of their products and services. Harnessing the Power of Social Media and Web Analytics documents high-quality research to empower businesses to derive intelligence from social media sites. These emerging technological tools have allowed businesses to quantify, understand, and respond to customers’ conversations about their corporate reputation and brands within online communities. This publication is ideal for academic and professional audiences interested in applications and practices of social media and web analytics in various industries.
  gartner data science quadrant: Applied Data Science in Tourism Roman Egger, 2022-01-31 Access to large data sets has led to a paradigm shift in the tourism research landscape. Big data is enabling a new form of knowledge gain, while at the same time shaking the epistemological foundations and requiring new methods and analysis approaches. It allows for interdisciplinary cooperation between computer sciences and social and economic sciences, and complements the traditional research approaches. This book provides a broad basis for the practical application of data science approaches such as machine learning, text mining, social network analysis, and many more, which are essential for interdisciplinary tourism research. Each method is presented in principle, viewed analytically, and its advantages and disadvantages are weighed up and typical fields of application are presented. The correct methodical application is presented with a how-to approach, together with code examples, allowing a wider reader base including researchers, practitioners, and students entering the field. The book is a very well-structured introduction to data science – not only in tourism – and its methodological foundations, accompanied by well-chosen practical cases. It underlines an important insight: data are only representations of reality, you need methodological skills and domain background to derive knowledge from them - Hannes Werthner, Vienna University of Technology Roman Egger has accomplished a difficult but necessary task: make clear how data science can practically support and foster travel and tourism research and applications. The book offers a well-taught collection of chapters giving a comprehensive and deep account of AI and data science for tourism - Francesco Ricci, Free University of Bozen-Bolzano This well-structured and easy-to-read book provides a comprehensive overview of data science in tourism. It contributes largely to the methodological repository beyond traditional methods. - Rob Law, University of Macau
  gartner data science quadrant: Supply Chain Analytics and Modelling Nicoleta Tipi, 2021-04-03 An incredible volume of data is generated at a very high speed within the supply chain and it is necessary to understand, use and effectively apply the knowledge learned from analyzing data using intelligent business models. However, practitioners and students in the field of supply chain management face a number of challenges when dealing with business models and mathematical modelling. Supply Chain Analytics and Modelling presents a range of business analytics models used within the supply chain to help readers develop knowledge on a variety of topics to overcome common issues. Supply Chain Analytics and Modelling covers areas including supply chain planning, single and multi-objective optimization, demand forecasting, product allocations, end-to-end supply chain simulation, vehicle routing and scheduling models. Learning is supported by case studies of specialist software packages for each example. Readers will also be provided with a critical view on how supply chain management performance measurement systems have been developed and supported by reliable and accurate data available in the supply chain. Online resources including lecturer slides are available.
  gartner data science quadrant: Multimedia Technologies in the Internet of Things Environment, Volume 3 Raghvendra Kumar, Rohit Sharma, Prasant Kumar Pattnaik, 2022-04-04 This book proposes a comprehensive overview of the state-of-the-art research work on multimedia analysis in IoT applications. This is a third volume by editors which provides theoretical and practical approach in the area of multimedia and IOT applications and performance analysis. Further, multimedia communication, deep learning models to multimedia data, and the new (IOT) approaches are also covered. It addresses the complete functional framework in the area of multimedia data, IoT, and smart computing techniques. It bridges the gap between multimedia concepts and solutions by providing the current IOT frameworks, their applications in multimedia analysis, the strengths and limitations of the existing methods, and the future directions in multimedia IOT analytics.
  gartner data science quadrant: Towards a Collaborative Society Through Creative Learning Therese Keane, Cathy Lewin, Torsten Brinda, Rosa Bottino, 2023-09-27 This book contains the revised selected, refereed papers from the IFIP World Conference on Computers in Education on Towards a Collaborative Society through Creative Learning, WCCE 2022, Hiroshima, Japan, August 20-24, 2022. A total of 61 papers (54 full papers and 7 short papers) were carefully reviewed and selected from 131 submissions. They were organized in topical sections as follows: ​ Digital Education and Computing in Schools, Digital Education and Computing in Higher Education, National Policies and Plans for Digital Competence.
  gartner data science quadrant: Analytics and Data Science Amit V. Deokar, Ashish Gupta, Lakshmi S. Iyer, Mary C. Jones, 2017-10-05 This book explores emerging research and pedagogy in analytics and data science that have become core to many businesses as they work to derive value from data. The chapters examine the role of analytics and data science to create, spread, develop and utilize analytics applications for practice. Selected chapters provide a good balance between discussing research advances and pedagogical tools in key topic areas in analytics and data science in a systematic manner. This book also focuses on several business applications of these emerging technologies in decision making, i.e., business analytics. The chapters in Analytics and Data Science: Advances in Research and Pedagogy are written by leading academics and practitioners that participated at the Business Analytics Congress 2015. Applications of analytics and data science technologies in various domains are still evolving. For instance, the explosive growth in big data and social media analytics requires examination of the impact of these technologies and applications on business and society. As organizations in various sectors formulate their IT strategies and investments, it is imperative to understand how various analytics and data science approaches contribute to the improvements in organizational information processing and decision making. Recent advances in computational capacities coupled by improvements in areas such as data warehousing, big data, analytics, semantics, predictive and descriptive analytics, visualization, and real-time analytics have particularly strong implications on the growth of analytics and data science.
  gartner data science quadrant: Institutional Research in South African HigherÿEducationÿ Jan Botha, Nicole J Muller, 2016-11-01 The book provides a thorough overview of Institutional Research (IR) ? i.e. applied higher education research undertaken within universities ? in South Africa. It is a collection of essays focusing on the character and institutional setting of IR; how IR is embedded into the mechanisms of steering, shaping and reforming higher education; and what the major results were of IR in select thematic areas. The book is a valuable resource for higher education researchers and social researchers in South Africa interested in higher education. It ÿalso deserves to be read by practitioners and policymakers in the field of higher education in South Africa. It serves as an interesting case study for higher education researchers all over the world.
  gartner data science quadrant: Financial Data Analytics Sinem Derindere Köseoğlu, 2022-04-25 ​This book presents both theory of financial data analytics, as well as comprehensive insights into the application of financial data analytics techniques in real financial world situations. It offers solutions on how to logically analyze the enormous amount of structured and unstructured data generated every moment in the finance sector. This data can be used by companies, organizations, and investors to create strategies, as the finance sector rapidly moves towards data-driven optimization. This book provides an efficient resource, addressing all applications of data analytics in the finance sector. International experts from around the globe cover the most important subjects in finance, including data processing, knowledge management, machine learning models, data modeling, visualization, optimization for financial problems, financial econometrics, financial time series analysis, project management, and decision making. The authors provide empirical evidence as examples of specific topics. By combining both applications and theory, the book offers a holistic approach. Therefore, it is a must-read for researchers and scholars of financial economics and finance, as well as practitioners interested in a better understanding of financial data analytics.
Magic Quadrant for Data Science and Machine-Learning …
Feb 22, 2018 · Gartner invited a diverse mix of data science platform vendors to participate in the evaluation process for potential inclusion in this Magic Quadrant, as data scientists have …

Gartner Research Methodologies Technology-related …
A companion to the Magic Quadrant and Critical Capabilities, the Gartner Evaluation Criteria document provides a baseline set of standards to help you make successful product …

Magic Quadrant for Data Integration Tools - Grey Wolf
Gartner defines data integration as the discipline comprising the architectural patterns, tools and methodologies that allow organizations to access, harmonize, transform, process and move …

Gartner Webinars - Amazon Web Services, Inc.
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Magic Quadrant for Data Science and Machine Learning …
source data, build models and operationalize machine learning. It will help them make the right choice from a crowded field in a maturing DSML pl. orks (including proprietary, partner …

IBM Positioned as a Leader in 2021 Gartner Magic Quadrant …
Mar 25, 2021 · Gartner has positioned IBM as a Leader in the newly published 2021 Gartner Magic Quadrant for Insight Engines1. This builds on the recent news that IBM was positioned …

Magic Quadrant for Analytics and Business Intelligence …
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Considering the expansion in market demand, and the evolution and innovation of technologies, Gartner changed the name of this Magic Quadrant from “Magic Quadrant for Data Quality …

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Data science platforms are engines for creating machine-learning solutions. Innovation in this market focuses on cloud, Apache Spark, automation, collaboration and artificial-intelligence …

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This Magic Quadrant evaluates vendors of data science and machine learning (DSML) platforms. Gar tner defines a DSML platform as a cor e product and suppor ting por tfolio of coherently …

FEATURES, BENEFITS AND FREQUENTLY ASKED …
The Gartner Magic Quadrant is established and proven, providing top global organizations with a snapshot of a market to guide their most important technology decisions.

Magic Quadrant for Analytics and Business Intelligence …
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Gartner’s visie op de ontwikkelingen van Data Science en …
Platforms heeft Gartner het 2020 Magic Quadrant for Data Science and Machine Learning Platforms gepresenteerd. Het marktlandschap voor Datascience (DS), Machine Learning (ML) …

Platforms Magic Quadrant for Data Science and Machine …
Data science and machine-learning platforms enable organizations to take an end-to-end approach to building and deploying data science models. This Magic Quadrant evaluates 16 …

Magic Quadrant for Data Science and Machine Learning
Data science and machine learning platforms allow insight-driv en decision making based on data science techniques via build, cust omize and deploy machine learning and generative AI …

Gartner Magic Quadrant
To ensure consistency in our ratings and placements, a formal process to create a Gartner Magic Quadrant is followed. These questions address what we hear most often from end users and …

Magic Quadrant for Data Quality Tools
Data quality tools are vital for digital business transformation, especially now that many have emerging features like automation, machine learning, business-centric workflows and cloud …

Magic Quadrant for Analytics and Business Intelligence …
This Magic Quadrant focuses on products that meet Gartner’s criteria for a modern analytics and BI platform (see “Technology Insight for Modern Analytics and Business Intelligence Platforms”).

Magic Quadrant for Data Science and Machine-Learning …
Feb 22, 2018 · Gartner invited a diverse mix of data science platform vendors to participate in the evaluation process for potential inclusion in this Magic Quadrant, as data …

Gartner Research Methodologies Technology-related insights for …
A companion to the Magic Quadrant and Critical Capabilities, the Gartner Evaluation Criteria document provides a baseline set of standards to help you make successful …

Magic Quadrant for Data Integration Tools - Grey Wolf
Gartner defines data integration as the discipline comprising the architectural patterns, tools and methodologies that allow organizations to access, harmonize, …

Gartner Webinars - Amazon Web Services, Inc.
1. ABI and Data Science and Machine Learning (DSML) worlds have collided. 2. ‘Generative analytics experiences’ enhance end-to-end, augmented analytics. 3. …

Magic Quadrant for Data Science and Machine Learning P…
source data, build models and operationalize machine learning. It will help them make the right choice from a crowded field in a maturing DSML pl. orks (including …