Managing Data Science
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Managing Data Science
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Author : Kirill Dubovikov
language : en
Publisher:
Release Date : 2019-11-12
Managing Data Science written by Kirill Dubovikov and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-12 with categories.
Understand data science concepts and methodologies to manage and deliver top-notch solutions for your organization Key Features Learn the basics of data science and explore its possibilities and limitations Manage data science projects and assemble teams effectively even in the most challenging situations Understand management principles and approaches for data science projects to streamline the innovation process Book Description Data science and machine learning can transform any organization and unlock new opportunities. However, employing the right management strategies is crucial to guide the solution from prototype to production. Traditional approaches often fail as they don't entirely meet the conditions and requirements necessary for current data science projects. In this book, you'll explore the right approach to data science project management, along with useful tips and best practices to guide you along the way. After understanding the practical applications of data science and artificial intelligence, you'll see how to incorporate them into your solutions. Next, you will go through the data science project life cycle, explore the common pitfalls encountered at each step, and learn how to avoid them. Any data science project requires a skilled team, and this book will offer the right advice for hiring and growing a data science team for your organization. Later, you'll be shown how to efficiently manage and improve your data science projects through the use of DevOps and ModelOps. By the end of this book, you will be well versed with various data science solutions and have gained practical insights into tackling the different challenges that you'll encounter on a daily basis. What you will learn Understand the underlying problems of building a strong data science pipeline Explore the different tools for building and deploying data science solutions Hire, grow, and sustain a data science team Manage data science projects through all stages, from prototype to production Learn how to use ModelOps to improve your data science pipelines Get up to speed with the model testing techniques used in both development and production stages Who this book is for This book is for data scientists, analysts, and program managers who want to use data science for business productivity by incorporating data science workflows efficiently. Some understanding of basic data science concepts will be useful to get the most out of this book.
Managing Your Data Science Projects
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Author : Robert de Graaf
language : en
Publisher: Apress
Release Date : 2019-06-08
Managing Your Data Science Projects written by Robert de Graaf and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-08 with Computers categories.
At first glance, the skills required to work in the data science field appear to be self-explanatory. Do not be fooled. Impactful data science demands an interdisciplinary knowledge of business philosophy, project management, salesmanship, presentation, and more. In Managing Your Data Science Projects, author Robert de Graaf explores important concepts that are frequently overlooked in much of the instructional literature that is available to data scientists new to the field. If your completed models are to be used and maintained most effectively, you must be able to present and sell them within your organization in a compelling way. The value of data science within an organization cannot be overstated. Thus, it is vital that strategies and communication between teams are dexterously managed. Three main ways that data science strategy is used in a company is to research its customers, assess risk analytics, and log operational measurements. These all require different managerial instincts, backgrounds, and experiences, and de Graaf cogently breaks down the unique reasons behind each. They must align seamlessly to eventually be adopted as dynamic models. Data science is a relatively new discipline, and as such, internal processes for it are not as well-developed within an operational business as others. With Managing Your Data Science Projects, you will learn how to create products that solve important problems for your customers and ensure that the initial success is sustained throughout the product’s intended life. Your users will trust you and your models, and most importantly, you will be a more well-rounded and effectual data scientist throughout your career. Who This Book Is For Early-career data scientists, managers of data scientists, and those interested in entering the field of data science
The Decision Maker S Handbook To Data Science
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Author : Stylianos Kampakis
language : en
Publisher: Apress
Release Date : 2019-11-26
The Decision Maker S Handbook To Data Science written by Stylianos Kampakis and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-26 with Computers categories.
Data science is expanding across industries at a rapid pace, and the companies first to adopt best practices will gain a significant advantage. To reap the benefits, decision makers need to have a confident understanding of data science and its application in their organization. It is easy for novices to the subject to feel paralyzed by intimidating buzzwords, but what many don’t realize is that data science is in fact quite multidisciplinary—useful in the hands of business analysts, communications strategists, designers, and more. With the second edition of The Decision Maker’s Handbook to Data Science, you will learn how to think like a veteran data scientist and approach solutions to business problems in an entirely new way. Author Stylianos Kampakis provides you with the expertise and tools required to develop a solid data strategy that is continuously effective. Ethics and legal issues surrounding data collection and algorithmic bias are some common pitfalls that Kampakis helps you avoid, while guiding you on the path to build a thriving data science culture at your organization. This updated and revised second edition, includes plenty of case studies, tools for project assessment, and expanded content for hiring and managing data scientists Data science is a language that everyone at a modern company should understand across departments. Friction in communication arises most often when management does not connect with what a data scientist is doing or how impactful data collection and storage can be for their organization. The Decision Maker’s Handbook to Data Science bridges this gap and readies you for both the present and future of your workplace in this engaging, comprehensive guide. What You Will Learn Understand how data science can be used within your business. Recognize the differences between AI, machine learning, and statistics. Become skilled at thinking like a data scientist, without being one. Discover how to hire and manage data scientists. Comprehend how to build the right environment in order to make your organization data-driven. Who This Book Is For Startup founders, product managers, higher level managers, and any other non-technical decision makers who are thinking to implement data science in their organization and hire data scientists. A secondary audience includes people looking for a soft introduction into the subject of data science.
Analytics And Knowledge Management
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Author : Suliman Hawamdeh
language : en
Publisher: CRC Press
Release Date : 2018-08-06
Analytics And Knowledge Management written by Suliman Hawamdeh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-06 with Computers categories.
The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics technique. Analytics and Knowledge Management examines the role of analytics in knowledge management and the integration of big data theories, methods, and techniques into an organizational knowledge management framework. Its chapters written by researchers and professionals provide insight into theories, models, techniques, and applications with case studies examining the use of analytics in organizations. The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics techniques. Analytics, on the other hand, is the examination, interpretation, and discovery of meaningful patterns, trends, and knowledge from data and textual information. It provides the basis for knowledge discovery and completes the cycle in which knowledge management and knowledge utilization happen. Organizations should develop knowledge focuses on data quality, application domain, selecting analytics techniques, and on how to take actions based on patterns and insights derived from analytics. Case studies in the book explore how to perform analytics on social networking and user-based data to develop knowledge. One case explores analyze data from Twitter feeds. Another examines the analysis of data obtained through user feedback. One chapter introduces the definitions and processes of social media analytics from different perspectives as well as focuses on techniques and tools used for social media analytics. Data visualization has a critical role in the advancement of modern data analytics, particularly in the field of business intelligence and analytics. It can guide managers in understanding market trends and customer purchasing patterns over time. The book illustrates various data visualization tools that can support answering different types of business questions to improve profits and customer relationships. This insightful reference concludes with a chapter on the critical issue of cybersecurity. It examines the process of collecting and organizing data as well as reviewing various tools for text analysis and data analytics and discusses dealing with collections of large datasets and a great deal of diverse data types from legacy system to social networks platforms.
Big Data And Data Science
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Author : Dhaanyalakshmi Ahuja
language : en
Publisher: Educohack Press
Release Date : 2025-01-03
Big Data And Data Science written by Dhaanyalakshmi Ahuja and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Computers categories.
Big Data and Data Science: Analytics for the Future dives into the fundamentals of big data and data science. We explain the data science life cycle and its major components, such as statistics and visualization, using various programming languages like R. As technology evolves, the significance of data science and big data analytics continues to grow, making this field increasingly important. Our book is designed in a reader-friendly manner, targeting newcomers to data science. Concepts are presented clearly and can be easily implemented through the procedures and algorithms provided. As data collection multiplies exponentially, analytics remains an evolving field with vast career opportunities. We cater to two types of readers: those skeptical about the benefits of big data and predictive analytics, and enthusiasts keen to explore current applications of these technologies. Big data is a fantastic choice for launching a career in IT, and this book equips you with the knowledge needed to succeed. We cover a broad spectrum of topics, ensuring a strong foundation in data science and big data analytics.
Advanced Digital Technologies In Financial And Business Management
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Author : Jyoti Batra Arora
language : en
Publisher: CRC Press
Release Date : 2025-07-11
Advanced Digital Technologies In Financial And Business Management written by Jyoti Batra Arora and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-11 with Business & Economics categories.
This new book explores emerging new technologies for the development of business and finance sectors, to strengthen economic growth, and to facilitate the efficiency and creation of new and innovative business and finance management applications. The book covers state-of-the-art technologies such as artificial intelligence and big data analytics in fintech and finance, blockchain technology in the insurance industry, the use of AI and data science in tax administration, the growing use of 6G in industrial automation, quantum machine learning in finance, the merging of AI and blockchain in auditing, and more. Chapters explore the collaboration between humans and machines, the application of data science and artificial intelligence in the retail sector, and AI and data science in business services with a focus on enhancing efficiency and driving innovation.
Digital Transformation In Accounting
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Author : Richard Busulwa
language : en
Publisher: Routledge
Release Date : 2021-05-30
Digital Transformation In Accounting written by Richard Busulwa and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-30 with Business & Economics categories.
Digital Transformation in Accounting is a critical guidebook for accountancy and digital business students and practitioners to navigate the effects of digital technology advancements, digital disruption, and digital transformation on the accounting profession. Drawing on the latest research, this book: Unpacks dozens of digital technology advancements, explaining what they are and how they could be used to improve accounting practice. Discusses the impact of digital disruption and digital transformation on different accounting functions, roles, and activities. Integrates traditional accounting information systems concepts and contemporary digital business and digital transformation concepts. Includes a rich array of real-world case studies, simulated problems, quizzes, group and individual exercises, as well as supplementary electronic resources. Provides a framework and a set of tools to prepare the future accounting workforce for the era of digital disruption. This book is an invaluable resource for students on accounting, accounting information systems, and digital business courses, as well as for accountants, accounting educators, and accreditation / advocacy bodies.
Big Data Management
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Author : Peter Ghavami
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2020-11-09
Big Data Management 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 2020-11-09 with Business & Economics categories.
Data analytics is core to business and decision making. The rapid increase in data volume, velocity and variety offers both opportunities and challenges. While open source solutions to store big data, like Hadoop, offer platforms for exploring value and insight from big data, they were not originally developed with data security and governance in mind. Big Data Management discusses numerous policies, strategies and recipes for managing big data. It addresses data security, privacy, controls and life cycle management offering modern principles and open source architectures for successful governance of big data. The author has collected best practices from the world’s leading organizations that have successfully implemented big data platforms. The topics discussed cover the entire data management life cycle, data quality, data stewardship, regulatory considerations, data council, architectural and operational models are presented for successful management of big data. The book is a must-read for data scientists, data engineers and corporate leaders who are implementing big data platforms in their organizations.
Handbook Of Education Policy Research
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Author : Lora Cohen-Vogel
language : en
Publisher: American Educational Research Association
Release Date : 2025-07-17
Handbook Of Education Policy Research written by Lora Cohen-Vogel and has been published by American Educational Research Association this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-17 with Education categories.
The second edition of the Handbook of Education Policy Research—the largest volume published in AERA’s history—addresses a variety of policy and contextual issues in early childhood, K–12, and postsecondary education that have received extensive empirical attention during the past 15 years. With the pandemic and social turmoil as a backdrop, the editors build on the breadth and depth of the first edition while expanding the scope of the project to include subjects, methods, theories, and analyses that have contributed powerfully to the study of education policy and politics in the 2010s and 2020s. The field has become more comprehensive and inclusive, and the authors represent a diversity of racial/ethnic and gender identities and intellectual and disciplinary orientations. Most chapters come from multiple authors, reflecting the multi-sourced development of research in education policy since the first volume was published. This compilation consists of 70 chapters and nine commentaries that map past, present, and future directions of the field and richly attend to critical issues of interest to students, researchers, policy makers, and practitioners.
A Beginner S Guide To Data Science
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Author : Enamul Haque
language : en
Publisher:
Release Date : 2023-01-06
A Beginner S Guide To Data Science written by Enamul Haque and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-06 with categories.
This book is designed for aspiring data scientists who want to start their careers in data science, even if they don't have coding skills. It provides a comprehensive introduction to the foundations of data science and its applications, using simple language that is easy for beginners to understand. No technical expertise is required to master the material in this book. It is an ideal resource for anyone looking to learn about data science in an accessible and straightforward way. Key features include: Introduction to data science History of data science Data science life-cycle Data science tools and technologies Data science methodology Data science models Developing data science business strategy Managing data science projects Becoming a data scientist, data engineer etc. Big data Data Mining Artificial intelligence Machine learning Deep learning Neural networks Mathematical analysis Statistical modelling Understanding the fundamentals of data science programming languages Database structures and principles Robotic Process Automation Data science acronyms You need to know And a lot more.