"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." (Xiuli He et al, "Supply Chain Analytics: Challenges and Opportunities", 2014)
"A collection of models, techniques and algorithms that focus on the issues of gathering, pre-processing, and making sense-out of large repositories of data, which are seen as 'data products'." (Alfredo Cuzzocrea & Mohamed M Gaber, "Data Science and Distributed Intelligence", 2015)
"Data science involves using methods to analyze massive amounts of data and extract the knowledge it contains. […] Data science is an evolutionary extension of statistics capable of dealing with the massive amounts of data produced today. It adds methods from computer science to the repertoire of statistics." (Davy Cielen et al, "Introducing Data Science", 2016)
"The workflows and processes involved in the creation and development of data products." (Benjamin Bengfort & Jenny Kim, "Data Analytics with Hadoop", 2016)
"The discipline of analysis that helps relate data to the events and processes that produce and consume it for different reasons." (Gregory Lampshire, "The Data and Analytics Playbook", 2016)
"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)." (Suren Behari, "Data Science and Big Data Analytics in Financial Services: A Case Study", 2016)
"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." (Babangida Zubairu, "Security Risks of Biomedical Data Processing in Cloud Computing Environment", 2018)
"Data science is a collection of techniques used to extract value from data. It has become an essential tool for any organization that collects, stores, and processes data as part of its operations. Data science techniques rely on finding useful patterns, connections, and relationships within data. Being a buzzword, there is a wide variety of definitions and criteria for what constitutes data science. Data science is also commonly referred to as knowledge discovery, machine learning, predictive analytics, and data mining. However, each term has a slightly different connotation depending on the context." (Vijay Kotu & Bala Deshpande, "Data Science" 2nd Ed., 2018)
"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." (Zhaohao Sun, "Intelligent Big Data Analytics: A Managerial Perspective", 2019)
"Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured similar to data mining." (K Hariharanath, "BIG Data: An Enabler in Developing Business Models in Cloud Computing Environments", 2019)
"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." (Maryna Nehrey & Taras Hnot, "Data Science Tools Application for Business Processes Modelling in Aviation", 2019)
"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." (Soraya Sedkaoui, "Big Data Analytics for Entrepreneurial Success", 2019)
"the study and application of techniques for deriving insights from data, including constructing algorithms for prediction. Traditional statistical science forms part of data science, which also includes a strong element of coding and data management." (David Spiegelhalter, "The Art of Statistics: Learning from Data", 2019)
"A relatively new term applied to an interdisciplinary field of study focused on methods for collecting, maintaining, processing, analyzing and presenting results from large datasets." (Osman Kandara & Eugene Kennedy, "Educational Data Mining: A Guide for Educational Researchers", 2020)
"Data Science is the branch of science that uses technologies to predict the upcoming nature of different things such as a market or weather conditions. It shows a wide usage in today’s world." (Kirti R Bhatele, "Data Analysis on Global Stratification", 2020)
"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." (Tanushri Banerjee & Arindam Banerjee, "Designing a Business Analytics Culture in Organizations in India", 2021)
"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." (Ahmad M Kabil, Integrating Big Data Technology Into Organizational Decision Support Systems, 2021)
Data Science is an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights." (R Suganya et al, "A Literature Review on Thyroid Hormonal Problems in Women Using Data Science and Analytics: Healthcare Applications", 2021)
"Data Science is the science and art of using computational methods to identify and discover influential patterns in data." (M Govindarajan, "Introduction to Data Science", 2021)
"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." (Pankaj Pathak, "A Survey on Tools for Data Analytics and Data Science", 2021)
"It is a science of multiple disciplines used for exploring knowledge from data using complex scientific algorithms and methods." (Vandana Kalra et al, "Machine Learning and Its Application in Monitoring Diabetes Mellitus", 2021)
"The concept that utilizes scientific and software methods, IT infrastructure, processes, and software systems in order to gather, process, analyze and deliver useful information, knowledge and insights from various data sources." (Nenad Stefanovic, "Big Data Analytics in Supply Chain Management", 2021)
"This is an evolving field that deals with the gathering, preparation, exploration, visualization, organisation, and storage of large groups of data and the extraction of valuable information from large volumes of data that may exist in an unorganised or unstructured form." (James O Odia & Osaheni T Akpata, "Role of Data Science and Data Analytics in Forensic Accounting and Fraud Detection", 2021)
"A field of study involving the processes and systems used to extract insights from data in all of its forms. The profession is seen as a continuation of the other data analysis fields, such as statistics." (Solutions Review)
"The discipline of using data and advanced statistics to make predictions. Data science is also focused on creating understanding among messy and disparate data. The “what” a scientist is tackling will differ greatly by employer." (KDnuggets)
"Unites statistical systems and processes with computer and information science to mine insights with structured and/or unstructured data analytics." (Accenture)
"Data science is a multidisciplinary approach to finding, extracting, and surfacing patterns in data through a fusion of analytical methods, domain expertise, and technology. This approach generally includes the fields of data mining, forecasting, machine learning, predictive analytics, statistics, and text analytics." (Tibco) [source]
"Data science is an interdisciplinary field that combines social sciences, advanced statistics, and computer engineering skills to acquire, store, organize, and analyze information across a variety of sources." (TDWI)
"Data science is the multidisciplinary field that focuses on finding actionable information in large, raw or structured data sets to identify patterns and uncover other insights. The field primarily seeks to discover answers for areas that are unknown and unexpected." (Sisense) [source]
"Data science is the practical application of advanced analytics, statistics, machine learning, and the associated activities involved in those areas in a business context, like data preparation for example." (RapidMiner) [source]
"Data Science unites statistical systems and processes with computer and information science to mine insights with structured and/or unstructured data analytics." (Accenture)
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