Data Science And Big Data Analytics Process And Practices
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Data Science And Big Data Analytics Process And Practices
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Author : Arun Kumar Mittapelly
language : en
Publisher: Academic Guru Publishing House
Release Date : 2025-03-21
Data Science And Big Data Analytics Process And Practices written by Arun Kumar Mittapelly and has been published by Academic Guru Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-21 with Study Aids categories.
“Data Science and Big Data Analytics” is a definitive resource for learning about data science techniques, methodologies, and the technologies that are shaping the future of data analysis. This book covers a broad spectrum of topics, from the fundamentals of data collection and preprocessing to advanced techniques in machine learning and predictive analytics. Designed with both beginners and seasoned professionals in mind, the book takes a structured approach, starting with essential concepts before progressing to more intricate topics like big data technologies (Hadoop, Spark), real-time analytics, and predictive modeling. Detailed explanations and practical examples ensure that readers can easily understand and apply the techniques discussed. Each chapter emphasises hands-on learning and provides practical insights that can be used in everyday business and technical applications. This book is particularly suited for individuals who are preparing to enter the data science field or those already working in industries like healthcare, finance, marketing, and supply chain management. It also addresses key challenges such as data privacy and ethical concerns in big data analytics, ensuring readers are well-prepared to navigate this complex and dynamic domain.
Data Science And Big Data Analytics Principles Techniques And Applications
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Author : Dr. Dhananjaya Reddy
language : en
Publisher: Academic Guru Publishing House
Release Date : 2024-10-25
Data Science And Big Data Analytics Principles Techniques And Applications written by Dr. Dhananjaya Reddy and has been published by Academic Guru Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-25 with Study Aids categories.
“Data Science and Big Data Analytics: Principles, Techniques, and Applications” is designed to provide a comprehensive introduction to the rapidly growing fields of data science and big data analytics. The book offers a balanced approach to both theoretical concepts and practical knowledge, making it ideal for learners at various levels—ranging from beginners to those seeking advanced understanding. By exploring topics such as data collection, preprocessing, machine learning, and big data technologies, the book lays the groundwork for understanding how large-scale data is managed and utilized in real-world applications. Without including case studies or examples, the text emphasizes key concepts, tools, and methodologies. The book also addresses ethical considerations and future trends in data science, making it a well-rounded resource for students, educators, and professionals aiming to grasp the essentials of the field.
Big Data Analytics Methods
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Author : Peter Ghavami
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2019-12-16
Big Data Analytics Methods written by Peter Ghavami and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-16 with Business & Economics categories.
Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensembles of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data visualization, prediction, optimization, artificial intelligence, regression analysis, the Cox hazard model and many analytics using case examples with applications in the healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services industries. This book's state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics.
Introduction To Data Science And Machine Learning
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Author : Keshav Sud
language : en
Publisher: BoD – Books on Demand
Release Date : 2020-03-25
Introduction To Data Science And Machine Learning written by Keshav Sud and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-25 with Computers categories.
Introduction to Data Science and Machine Learning has been created with the goal to provide beginners seeking to learn about data science, data enthusiasts, and experienced data professionals with a deep understanding of data science application development using open-source programming from start to finish. This book is divided into four sections: the first section contains an introduction to the book, the second covers the field of data science, software development, and open-source based embedded hardware; the third section covers algorithms that are the decision engines for data science applications; and the final section brings together the concepts shared in the first three sections and provides several examples of data science applications.
Data Science Concepts And Techniques With Applications
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Author : Usman Qamar
language : en
Publisher: Springer Nature
Release Date : 2023-04-02
Data Science Concepts And Techniques With Applications written by Usman Qamar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-02 with Computers categories.
This textbook comprehensively covers both fundamental and advanced topics related to data science. Data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. The chapters of this book are organized into three parts: The first part (chapters 1 to 3) is a general introduction to data science. Starting from the basic concepts, the book will highlight the types of data, its use, its importance and issues that are normally faced in data analytics, followed by presentation of a wide range of applications and widely used techniques in data science. The second part, which has been updated and considerably extended compared to the first edition, is devoted to various techniques and tools applied in data science. Its chapters 4 to 10 detail data pre-processing, classification, clustering, text mining, deep learning, frequent pattern mining, and regression analysis. Eventually, the third part (chapters 11 and 12) present a brief introduction to Python and R, the two main data science programming languages, and shows in a completely new chapter practical data science in the WEKA (Waikato Environment for Knowledge Analysis), an open-source tool for performing different machine learning and data mining tasks. An appendix explaining the basic mathematical concepts of data science completes the book. This textbook is suitable for advanced undergraduate and graduate students as well as for industrial practitioners who carry out research in data science. They both will not only benefit from the comprehensive presentation of important topics, but also from the many application examples and the comprehensive list of further readings, which point to additional publications providing more in-depth research results or provide sources for a more detailed description of related topics. "This book delivers a systematic, carefully thoughtful material on Data Science." from the Foreword by Witold Pedrycz, U Alberta, Canada.
Clinical Analytics And Data Management For The Dnp Second Edition
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Author : Martha L. Sylvia
language : en
Publisher: Springer Publishing Company
Release Date : 2018-03-28
Clinical Analytics And Data Management For The Dnp Second Edition written by Martha L. Sylvia and has been published by Springer Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-28 with Medical categories.
Praise for the First Edition: “DNP students may struggle with data management, since their projects are not research, but quality improvement, and this book covers the subject well. I recommend it for DNP students for use during their capstone projects." Score: 98, 5 Stars --Doody's Medical Reviews This is the only text to deliver the strong data management knowledge and skills that are required competencies for all DNP students. It enables readers to design data tracking and clinical analytics in order to rigorously evaluate clinical innovations/programs for improving clinical outcomes, and to document and analyze change. The second edition is greatly expanded and updated to address major changes in our health care environment. Incorporating faculty and student input, it now includes modalities such as SPSS, Excel, and Tableau to address diverse data management tasks. Eleven new chapters cover the use of big data analytics, ongoing progress towards value-based payment, the ACA and its future, shifting of risk and accountability to hospitals and clinicians, advancement of nursing quality indicators, and new requirements for Magnet certification. The text takes the DNP student step by step through the complete process of data management from planning to presentation, and encompasses the scope of skills required for students to apply relevant analytics to systematically and confidently tackle the clinical interventions data obtained as part of the DNP student project. Of particular value is a progressive case study illustrating multiple techniques and methods throughout the chapters. Sample data sets and exercises, along with objectives, references, and examples in each chapter, reinforce information. Key Features: Provides extensive content for rigorously evaluating DNP innovations/projects Takes DNP students through the complete process of data management from planning through presentation Includes a progressive case study illustrating multiple techniques and methods Offers very specific examples of application and utility of techniques Delivers sample data sets, exercises, PowerPoint slides and more, compiled in Supplemental Materials and an Instructor Manual
Portfolio Management In Practice Volume 1
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Author : CFA Institute
language : en
Publisher: John Wiley & Sons
Release Date : 2020-11-24
Portfolio Management In Practice Volume 1 written by CFA Institute and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-24 with Business & Economics categories.
Portfolio Management in Practice, Volume 1: Investment Management delivers a comprehensive overview of investment management for students and industry professionals. As the first volume in the CFA Institute’s new Portfolio Management in Practice series, Investment Management offers professionals looking to enhance their skillsets and students building foundational knowledge an essential understanding of key investment management concepts. Designed to be an accessible resource for a wide range of learners, this volume explores the full portfolio management process. Inside, readers will find detailed coverage of: Forming capital market expectations Principles of the asset allocation process Determining investment strategies within each asset class Integrating considerations specific to high net worth individuals or institutions into chosen strategies And more To apply the concepts outlined in the Investment Management volume, explore the accompanying Portfolio Management in Practice, Volume 1: Investment Management Workbook. The perfect companion resource, this workbook aligns chapter-by-chapter with Investment Management for easy referencing so readers can draw connections between theoretical content and challenging practice problems. Featuring contributions from the CFA Institute’s subject matter experts, Portfolio Management in Practice, Volume 1: Investment Management distills the knowledge forward-thinking professionals will need to succeed in today’s fast-paced financial world.
Big Data Science And Analytics For Smart Sustainable Urbanism
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Author : Simon Elias Bibri
language : en
Publisher: Springer
Release Date : 2019-05-30
Big Data Science And Analytics For Smart Sustainable Urbanism written by Simon Elias Bibri and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-30 with Social Science categories.
We are living at the dawn of what has been termed ‘the fourth paradigm of science,’ a scientific revolution that is marked by both the emergence of big data science and analytics, and by the increasing adoption of the underlying technologies in scientific and scholarly research practices. Everything about science development or knowledge production is fundamentally changing thanks to the ever-increasing deluge of data. This is the primary fuel of the new age, which powerful computational processes or analytics algorithms are using to generate valuable knowledge for enhanced decision-making, and deep insights pertaining to a wide variety of practical uses and applications. This book addresses the complex interplay of the scientific, technological, and social dimensions of the city, and what it entails in terms of the systemic implications for smart sustainable urbanism. In concrete terms, it explores the interdisciplinary and transdisciplinary field of smart sustainable urbanism and the unprecedented paradigmatic shifts and practical advances it is undergoing in light of big data science and analytics. This new era of science and technology embodies an unprecedentedly transformative and constitutive power—manifested not only in the form of revolutionizing science and transforming knowledge, but also in advancing social practices, producing new discourses, catalyzing major shifts, and fostering societal transitions. Of particular relevance, it is instigating a massive change in the way both smart cities and sustainable cities are studied and understood, and in how they are planned, designed, operated, managed, and governed in the face of urbanization. This relates to what has been dubbed data-driven smart sustainable urbanism, an emerging approach based on a computational understanding of city systems and processes that reduces urban life to logical and algorithmic rules and procedures, while also harnessing urban big data to provide a more holisticand integrated view or synoptic intelligence of the city. This is increasingly being directed towards improving, advancing, and maintaining the contribution of both sustainable cities and smart cities to the goals of sustainable development. This timely and multifaceted book is aimed at a broad readership. As such, it will appeal to urban scientists, data scientists, urbanists, planners, engineers, designers, policymakers, philosophers of science, and futurists, as well as all readers interested in an overview of the pivotal role of big data science and analytics in advancing every academic discipline and social practice concerned with data–intensive science and its application, particularly in relation to sustainability.
Towards Digital Intelligence Society
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Author : Ján Paralič
language : en
Publisher: Springer Nature
Release Date : 2020-12-21
Towards Digital Intelligence Society written by Ján Paralič and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-21 with Technology & Engineering categories.
This book aims to provide readers with up-to-date knowledge on how to make these technologies smarter. Humanity is now going through difficult times to fight the Covid-19 pandemic. Simultaneously, in these difficult times of physical separation, we can also realize how much digital society technology helps us cope with many difficulties that bring us this time. The authors focus on selected research challenges for intelligent digital society and state-of-the-art methods of how to face them. The book’s subtitle suggests that a core concept that the reader can study from various points of view in particular book chapters is the knowledge. The knowledge that can help us intelligently face different digital society challenges (Part I of this book); the knowledge extracted from available big data employing intelligent analysis techniques (Part II). For efficient processing and analysis of data, there is a strong need for smart data and information modeling techniques (Part III).
Big Data Analytics Techniques For Market Intelligence
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Author : Darwish, Dina
language : en
Publisher: IGI Global
Release Date : 2024-01-04
Big Data Analytics Techniques For Market Intelligence written by Darwish, Dina and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-04 with Computers categories.
The ever-expanding realm of Big Data poses a formidable challenge for academic scholars and professionals due to the sheer magnitude and diversity of data types, along with the continuous influx of information from various sources. Extracting valuable insights from this vast and complex dataset is crucial for organizations to uncover market intelligence and make informed decisions. However, without the proper guidance and understanding of Big Data analytics techniques and methodologies, scholars may struggle to navigate this landscape and maximize the potential benefits of their research. In response to this pressing need, Professor Dina Darwish presents Big Data Analytics Techniques for Market Intelligence, a groundbreaking book that addresses the specific challenges faced by scholars and professionals in the field. Through a comprehensive exploration of various techniques and methodologies, this book offers a solution to the hurdles encountered in extracting meaningful information from Big Data. Covering the entire lifecycle of Big Data analytics, including preprocessing, analysis, visualization, and utilization of results, the book equips readers with the knowledge and tools necessary to unlock the power of Big Data and generate valuable market intelligence. With real-world case studies and a focus on practical guidance, scholars and professionals can effectively leverage Big Data analytics to drive strategic decision-making and stay at the forefront of this rapidly evolving field.