Data Science and Data Analytics Opportunities and Challenges
Data Science and Data Analytics Opportunities and Challenges by Amit Kumar Tyagi, published by CRC Press in 2021, is a comprehensive exploration of the multi-disciplinary field of data science. This edition, consisting of 464 pages, delves into the methods, processes, and algorithms used to extract knowledge from both structured and unstructured data. The book emphasizes the importance of data science in the context of Artificial Intelligence and highlights the role of data analytics in uncovering hidden patterns and trends.
Readers will find a detailed examination of the various applications and challenges associated with data science, including issues related to complexity, scalability, and privacy. The text covers essential tools and techniques, such as Hadoop and R, while addressing the significant concerns that arise in the analysis of large datasets. Additionally, the book discusses the application of data science across diverse fields, including agriculture, healthcare, and education, making it a valuable resource for academicians, data scientists, and professionals seeking to enhance productivity through data-driven strategies.
Official synopsis Publisher
Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured (labeled) and unstructured (unlabeled) data. It is the future of Artificial Intelligence (AI) and a necessity of the future to make things easier and more productive. In simple terms, data science is the discovery of data or uncovering hidden patterns (such as complex behaviors, trends, and inferences) from data. Moreover, Big Data analytics/data analytics are the analysis mechanisms used in data science by data scientists. Several tools, such as Hadoop, R, etc., are used to analyze this large amount of data to predict valuable information and for decision-making. Note that structured data can be easily analyzed by efficient (available) business intelligence tools, while most of the data (80% of data by 2020) is in an unstructured form that requires advanced analytics tools. But while analyzing this data, we face several concerns, such as complexity, scalability, privacy leaks, and trust issues.
Data science helps us to extract meaningful information or insights from unstructured or complex or large amounts of data (available or stored virtually in the cloud). Data Science and Data Analytics: Opportunities and Challenges covers all possible areas, applications with arising serious concerns, and challenges in this emerging field in detail with a comparative analysis/taxonomy.
FEATURES
- Gives the concept of data science, tools, and algorithms that exist for many useful applications
- Provides many challenges and opportunities in data science and data analytics that help researchers to identify research gaps or problems
- Identifies many areas and uses of data science in the smart era
- Applies data science to agriculture, healthcare, graph mining, education, security, etc.
Academicians, data scientists, and stockbrokers from industry/business will find this book useful for designing optimal strategies to enhance their firm’s productivity.
Publisher
Topics
FAQ
What is “Data Science and Data Analytics Opportunities and Challenges” about?
Who is the author of “Data Science and Data Analytics Opportunities and Challenges”?
When was “Data Science and Data Analytics Opportunities and Challenges” published?
What is the ISBN for “Data Science and Data Analytics Opportunities and Challenges”?
What are the book details (language, pages, edition)?
