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What is Data Science

Encyclopedia of Organizational Knowledge, Administration, and Technology
Data science is a multi-disciplinary field that follows scientific approaches, methods, and processes to extract knowledge and insights from structured, semi-structured and unstructured data.
Published in Chapter:
Integrating Big Data Technology Into Organizational Decision Support Systems
Ahmad M. Kabil (University of Wisconsin-Whitewater, USA)
DOI: 10.4018/978-1-7998-3473-1.ch078
Abstract
With the growing trend of global competitiveness and business complexity, the need arises for integrating BDTs in the design of ODSS. BDTs enable ODSS to deal with data of volume, variety, and velocity beyond the capability of traditional databases and data-warehouses in ODSS. The basic modules of updated ODSS with BDT are presented as a conceptual design, which provides a general foundation for the detailed design and implementation of an application. The validation of the proposed conceptual design is conducted on a test-case based upon the BSC perspectives as well as requirements common for ODSS scenarios. The results show that each requirement of the system is supported by a set of integrated modules in a balanced way. The modules of the highest contribution in the conceptual design are the modules most related to BDT. The initial stages of the implementation of the system are given.
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Meet Industry Needs in the Big Data Era: Data Science Curricula Development
A branch of computer science that utilizes mathematical analytical methods to study big data in order to retrieve useful information.
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Introduction to Data Science
Data Science is the science and art of using computational methods to identify and discover influential patterns in data.
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Orienting Data Services in the Library: Evolution of a Digital Scholarship Services Department
An interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge from data and to apply that knowledge across a broad range of domains.
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Big Data Applications in Business
It is a new discipline that combines elements of mathematics, statistics, computer science, and data visualization. The objective is to extract information from data sources. In this sense, data science is devoted to database exploration and analysis. This discipline has recently received much attention due to the growing interest in big data.
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Pestel Analysis and the Porter's Five Forces: An Integrated Model of Strategic Sectors
The use of statistics and artificial intelligence to handle large amounts of data for advanced analysis.
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Data Science and Big Data Analytics in Financial Services: A Case Study
The extraction of knowledge from large volumes of unstructured data which is a continuation of the field data mining and predictive analytics, also known as knowledge discovery and data mining (KDD).
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A Meta-Analytical Review of Deep Learning Prediction Models for Big Data
Data science is word derived from data and science which include statistics, scientific methods, artificial intelligence, data analysis in order to extract information from data.
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Data Science Tools Application for Business Processes Modelling in Aviation
Is a broad field that refers to the collective processes, theories, concepts, tools and technologies that enable the review, analysis, and extraction of valuable knowledge and information from raw data. It is geared toward helping individuals and organizations make better decisions from stored, consumed and managed data.
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Toward the 4th Agenda 2030 Goal: AI Support to Executive Functions for Inclusions
Drawing from statistics, computer science and information science, this interdisciplinary field aims to use a variety of scientific methods, processes, and systems to solve problems involving data.
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Big Data Analytics for Smart Airport Management
Is a field that builds on and synthesizes a number of relevant disciplines and bodies of knowledge, including statistics, informatics, computing, communication, management, and sociology to translate data into information, knowledge, insight, and intelligence for improving innovation, productivity and decision making.
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Understanding Data Analytics Is Good but Knowing How to Use It Is Better!
It is a new discipline that combines elements of mathematics, statistics, computer science, and data visualization. The objective is to extract information from data sources. In this sense, data science is devoted to database exploration and analysis. This discipline has recently received much attention due to the growing interest in big data.
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A Literature Review on Thyroid Hormonal Problems in Women Using Data Science and Analytics: Healthcare Applications
Data Science is an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights.
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A Survey on Tools for Data Analytics and Data Science
Data science is the study of data. It involves developing methods of recording, storing, and analyzing data to effectively extract useful information. The goal of data science is to gain insights and knowledge from any type of data—both structured and unstructured.
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Security Risks of Biomedical Data Processing in Cloud Computing Environment
A knowledge acquisition from data through scientific method that comprises systematic observation, experiment, measurement, formulation, and hypotheses testing with the aim of discovering new ideas and concepts.
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Demand Forecasting Models With Time Series and Random Forest
An interdisciplinary field of study of data in relation to mathematics, statistics, operations research, data analysis, data mining, machine learning, computer science, engineering, visualization, data privacy, and big data.
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Interdisciplinary Application of Machine Learning, Data Science, and Python for Cricket Analytics
A multidisciplinary field that uses statistical and computational methods to extract knowledge and insights from data.
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Applying Intelligent Big Data Analytics in a Smart Airport Business: Value, Adoption, and Challenges
Is a field that builds on and synthesizes a number of relevant disciplines and bodies of knowledge, including statistics, informatics, computing, communication, management, and sociology to translate data into information, knowledge, insight, and intelligence for improving innovation, productivity and decision making.
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Is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract or extrapolate knowledge and insights from noisy, structured and unstructured data.
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With the increase in the amount of data captured by organizations, the various forms of structured and unstructured captured and the speed and frequency of it, significance of data science has increased over time. Data science is a methodical form of integrating statistics, algorithms, scientific methods, models and visualization methods for interpretation of outcomes in organizational problem solving and fact based decision making.
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Emerging Tools and Technologies in Data Science
The field of knowledge dealing with the total processing viz. collection, classification, comprehension, interpretation, etc., of raw facts in any discipline to convert those into the required information to be used by different government, non-government, non-profit, profit or business organizations working in or involved with the corresponding discipline, to make informative decision on the basis of authentic data. Using this sorts of data supports to make data based decisions is known as Decision Support System (DSS)
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The Contribution of Data Science Applied to Customer Relationship Management: A Systematic Literature Review
Recent popular field related to business analytics research and its intelligent techniques applied to big data.
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Machine Learning and Its Application in Monitoring Diabetes Mellitus
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Improving Transportation Planning Using Machine Learning
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A set of quantitative and qualitative methods that support and guide the extraction of information and knowledge from data to solve relevant problems and predict outcomes.
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Artificial Intelligence a Driver for Digital Transformation
Composed by mathematics, statistics, probability, computing, and data visualization to extract knowledge from a heterogeneous set of data (images, sound, text, genomic data, social network links, physical measurements, and others sources).
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