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Data Science and Data Analytics
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Data Science and Data Analytics : Opportunities and Challenges

Book Details

Format Hardback or Cased Book
ISBN-10 0367628821
ISBN-13 9780367628826
Publisher Taylor & Francis Ltd
Imprint Chapman & Hall/CRC
Country of Manufacture GB
Country of Publication GB
Publication Date Sep 23rd, 2021
Print length 464 Pages
Weight 1,066 grams
Dimensions 18.20 x 26.10 x 3.50 cms
Product Classification: Databases
Ksh 27,900.00
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Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. This book covers all the possible areas, applications with arising serious concerns, and challenges towards this emerging area/field in detail.

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.


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