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What is Big Data

Handbook of Research on Emerging Trends and Technologies in Librarianship
Data with greater variety, volume, and velocity that traditional data processing software cannot manage.
Published in Chapter:
Past, Present, and Future of Artificial Intelligence in Library Services
Ambar Yoganingrum (Research Center for Informatics, National Research and Innovation Agency, Indonesia), Rulina Rachmawati (Repository, Multimedia and Scientific Publications, National Research and Innovation Agency, Indonesia), and Koharudin Koharudin (Department of Computer Science, IPB University, Indonesia & Bureau for Organization and Human Resources, National Research and Innovation Agency, Indonesia)
DOI: 10.4018/978-1-7998-9094-2.ch007
Abstract
In the past, human imagination about intelligent machines was only found in the science fiction of storybooks and films. Today, artificial intelligence (AI) can be found in people's daily lives. Various professions should prepare to face the automation era in the future. Libraries may be one of the slowest institutions to develop AI. Gradually, the institution adopts it for their services. Many papers focus on AI development in libraries, but the opportunities and challenges for librarians to face the era of automation are essential to discuss. This chapter provides insights into the professions that librarians can offer. First, this chapter provides information on the history and development of AI in library services. Then, based on bibliometric analysis, this chapter discusses AI trends in library services. Next, this chapter conducts a systematic review and presents the types of AI developed over time for library services. Finally, this chapter discusses the types of jobs, expertise, and skills that librarians can develop in the robotics era in the future.
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Data, Knowledge, and Intelligence
Large amounts of data generated and stored by an enterprise, often in the areas of operations, transactions, and/or communications.
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Using Big Data in Healthcare
Any kind of data characterized by high volume, variety and/or velocity, which are difficult to process using traditional database management tools or data processing applications.
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Fintech Ecosystem and Banking: The Case of Turkey
Big data is an extremely large set of data that allows computational analysis to reveal particular human behavior, trends, and relationships.
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Reading Data Possibilities From an LMS Data Portal Data Dictionary
A relatively large amount of data, defined sometimes as over a million rows of data or a certain size of data (such as by terabytes and petabytes).
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Challenges in Big Data Analysis
Big data hold great promises for discovering subtle population patterns and heterogeneities that are not possible with small-scale data.
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Applying Intelligent Big Data Analytics in a Smart Airport Business: Value, Adoption, and Challenges
Is data with at least one of the ten big characteristics, consisting of big volume, big velocity, big variety, big veracity, big intelligence, big analytics, big infrastructure, big service, big value, and big market.
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Enhancing Online Repurchase Intention via Application of Big Data Analytics in E-Commerce
Big data is a combination of structured and unstructured data which is abundant in quantity, variety as well as the rate at which it gets generated resulting in a complex data set which cannot be stored, managed and processed by conventional statistical tools.
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Philosophy in the Knowledge Structure Pyramid: Knowledge Elicitation and Management
Extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations.
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Integration of Data Mining and Business Intelligence in Big Data Analytics: A Research Agenda on Scholarly Publications
Is enormous data set (mostly unstructured data) that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to interactions.
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Challenges to Records and Information Management in the Fourth Industrial Revolution
This expression describes the large volume of both structured and unstructured data that is created in an organization or business. Data grow exponentially, making it difficult to manage them. Traditional data management tools are unable to store or process data efficiently, thus new systems and tools are necessary.
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Big Data Visualization of Association Rules and Frequent Patterns
High-velocity, valuable, and/or multi-variety data with volumes beyond the ability of commonly used software to capture, manage, and process within a tolerable elapsed time. These Big Data necessitate new forms of processing to deliver high veracity (and low vulnerability) and to enable enhanced decision making, insight, knowledge discovery, and process optimization.
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Platform for Citizen Engagement for Good Governance in India: A Case Study of MyGov.in
It is an all-encompassing term for any collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications.
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Social Media Analytics for Maintaining Financial Stability
This is data characterized by its large volume, wide variety, and high velocity. Volume refers to high quantity of data usually running into terabytes. The data is not only numbers or text, but can include images, videos, etc., making it very varied and the data is generated rapidly which is called its high velocity.
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Challenges of Design Thinking in the Innovation of Individuals and Organizations
Is the area of knowledge that studies how to treat, analyze, and obtain information from data sets that are too large to be analyzed by traditional systems.
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Massive Digital Libraries (MDLs) and the Impact of Mass-Digitized Book Collections
The large-scale aggregation of data from software and wired devices, used for the purposes of analyzing systems or user behavior; it is characterized by its large volume, wide variety, velocity (or speed of transfer), its increased variability, and undetermined veracity.
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Analysis of the 5Vs of Big Data in Virtual Travel Organizations
The data which are not possible to be stored in relational databases at low cost and cannot be analyzed by classical methods, due to its volume and characteristics.
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The Impact of the Impact of Meta-Data Mining From the SoReCom “A.S. de Rosa” @-Library
According to some sources ( Boyd & Crawford, 2012 ; Mayer-Schönberger & Cukier, 2013 ) data volumes in the range of petabytes and beyond, which exceed the capacity of most current online storage and processing systems; critical issues related to big data include their volume, velocity, variety, value and veracity. However according to Parks (2014 : 255) data volume does not qualify in itself the “big data”, because the criteria should be relative to the “representativeness” of the specific field analysed.
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Driving Big Data with Hadoop Technologies
Data that spans over 3 Vs namely Volume, Variety and Velocity.
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Ethical Issues in Transhumanism
Is a concept related to dealing with really high amounts of data. Traditional databases can not store and analyze such big amounts of data.
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Marketing Management in Retail Customer Satisfaction: Opportunity and Challenges
It is the area of knowledge that studies how to treat, analyze and obtain information from very large data sets.
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Digital Transformation: Impact of 5G Technology in Supply Chain Industry
Is an evolving term that describes any voluminous amount of structured, semi-structured, and unstructured data that has the potential to be mined for information.
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Recommendation Systems
Big data also known as mega-data refers to all the digital data produced by the use of new technologies for personal or professional purposes.
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Data Science and Big Data Analytics in Financial Services: A Case Study
A broad term for large and complex data sets that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, and information privacy. The term often refers simply to the use of predictive analytics or other certain advanced methods to extract value from data, and seldom to a particular size of data set.
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Big Data-Driven Socioeconomic Development: An Interdisciplinary Approach
Data with at least one of the ten big characteristics consisting of big volume, big velocity, big variety, big veracity, big intelligence, big analytics, big infrastructure, big service, big value, and big market.
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Approaching Information Architecture for a Market Intelligence System Based on Emerging Technologies
Collaborative analysis done from structured (formally, predictable and formatted) and unstructured (posts, informal communication, social media usage) data regarding one specific topic.
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Knowledge Management and the Digital Native Enterprise
Data sets created by the convergence of various devices, equipment, and systems and that are too complex for traditional data processing software.
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Use of Big Data Analytics by Tax Authorities
The concept that near-infinite storage and computer processing has permitted the mass collection and storage of information about every aspect of our lives.
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Machine Learning in the Catering Industry
Datasets that are large and complex.
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Personal Data Privacy and Protection in the Meeting, Incentive, Convention, and Exhibition (MICE) Industry
In MICE industry, it is a common tool in following and tracking some useful information in regards to reaching the targeted meetings’ location history, subject details, national representatives, local ambassadors, hosting organizations and contact details of sponsors that supported those meetings, events or exhibitions.
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The Impact of Procedural Law on Artificial Intelligence by Improving the Healthcare Systems
Large and complicated data sets that cannot be processed or evaluated using conventional data processing methods are referred to as “big data.” In order to extract insights and value from data, one must employ specialized tools and procedures that can handle its size, diversity, and velocity.
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Foundational Theory: A New Conceptualization of Relevant Ideas
Very large data sets. These are used in higher education in a number of ways. Most relevant to this chapter are the ways they are used to anticipate students’ needs, choices, risks, etc.
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Meet Industry Needs in the Big Data Era: Data Science Curricula Development
Extremely large dataset that are generated in the digital age, which contains hidden useful information that can only be mined with modern computing technologies. Big data are usually unstructured have 5Vs property (volume, variety, velocity, value, and veracity).
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Ethical Aspects of Information-Based Medicine (With a Focus on Mental Health)
Datasets of diverse types and formats with various non-standard properties, such as large volume, enormous complexity, or heterogeneous quality.
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Unethical Advertising Techniques and Their Impact on Consumer Shopping Habits
Data users leave behind when using different apps connected to the Internet. Collecting these data in real time allows us to identify crucial user characteristics that can be used for customising marketing content and strategies. Marketing is only one possible way to use big data.
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Big Data Analytics for Smart Airport Management
Is data with at least one of the ten big characteristics consisting of big volume, big velocity, big variety, big veracity, big intelligence, big analytics, big infrastructure, big service, big value, and big market.
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Big Data Issues and Challenges
The volume of data that is just beyond technology’s capability to store, manage and process efficiently.
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Current and Future Years of E-Commerce
Datasets whose size, speed and variety are beyond the ability of typical database software tools to capture, store, administer, and analyze.
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Data Analysis and Integration in Healthcare
Consists of large data sets that can be analyzed via computers to reveal trends, patterns, and associations, made up of five key parts: volume, variety, velocity, veracity, and value.
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What Do Facebook Users Feel About Facebook Advertising?: Using an Experience Sampling Method (ESM) to Explore Their Digital Advertising Experiences
A term that defines a large dataset that produces in the size of collected data over time. It refers to the size of dataset that surpasses the capturing, storage, management, and analysis of traditional databases. The term refers to the dataset that has huge, more diverse, and multifaceted structure, accompanies by difficulties of data storage, analysis, and visualization. Big Data are characterized with the commonly known attributes: high-volume, -velocity, and –variety information assets.
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Apollo Hospital's Proposed Use of Big Data Healthcare Analytics
Big data is the term used to describe data sets that are too big or complicated for conventional data-processing application software to handle. While data with more complexity may result in a higher false discovery rate, data with more entries give better statistical power.
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Security and Privacy Issues of Big Data
The term that represents data sets that are extremely large to handle through traditional methods. Big data represents information that has such a high volume, velocity, variety, variability, veracity and complexity that require specific mechanisms in order to produce value from it.
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Digital Technology Advancements in Knowledge Management in Domestic Tour Products in the Russian Federation: Theoretical and Methodological Aspects
Is extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.
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Learning Management System 2.0: Higher Education
Big data is a huge amount of data that able to capture, link, collect, store, analized, and organize to provide value for the users.
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Distributed Programming Models for Big Data Analytics
Data that is so large and complex that it cannot be processed using traditional data processing tools or applications.
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Future Expectations About Big Data Analytics
It refers to large volume of data and has characteristics such as volume, variety and veracity etc.
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Innovation in Sustainability of Tourism After the COVID-19 Pandemic
It is the form of the data that has been analyzed, classified, and transformed into a meaningful and processable form.
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Real World Applications: Using Technology to Improve Supply Chain Management and Total Asset Visibility (TAV)
Extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.
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New Visual Literacies and Competencies for Education and the Workplace
Large or complex datasets that are too difficult to easily analyze with traditional processes including the utilization of predictive analysis for decision making.
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Unleashing the Convergence of Cloud Computing With Internet of Things: Drivers for Integration
Is an extremely large amount and varied data sets that may be analyzed computationally to unearth valuable information patterns, trends, relations, and associations, especially relating to human treatments, behaviour and interactions that can help institutions make informed decisions.
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Social Networks on the Internet: Dissemination and Communication of Scientific Knowledge
Refers to the massive amount of data generated and collected through various digital sources and platforms.
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Information Technology in the Search for Employment: Artificial Intelligence to Find the Best Job
As with the concept of “artificial intelligence”, there is a great variety of definitions that different authors have proposed for the concept of Big Data, a term whose use is relatively recent. A simple way to define it is as large sets of data, structured or unstructured, that can come from different sources and in different formats and that have the potential to be analyzed by computer techniques to extract information that is difficult to obtain directly.
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Big Data in Business: Digital Transformation for Enhanced Decision-making and Superior Customer Experience
Big data refers to the very large and diverse sets of structured, semi-structured and unstructured digital data from different sources that accumulate and grow very rapidly on continuous basis. Big data technologies enable enhanced decision making in various types of businesses.
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A Framework for Longitudinal Analysis of University Spin-Offs
Very large sets of data that can only be stored, used, and analyzed with the help of technological tools and methods.
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Big Data Transforming Small and Medium Enterprises
Data sets that are too large and complex to handle with traditional information technology tools.
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Artificial Intelligence and K-12: How to Explain?
A term that describes the large, diverse set of information.
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Big Data, Semantics, and Policy-Making: How Can Data Dynamics Lead to Wiser Governance?
Enormous amount of unstructured, heterogeneous and distributed data that is constantly changing over time and depending on the surrounding context. Big data can be seen as both a resource and a process, both of which are linked to the different interactions occurring on the web.
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Analysis of Big Data
Big data is a discipline that deals with methods for analysing, methodically extracting information from, or otherwise dealing with data volumes that are too massive or complicated for typical data-processing application software to handle.
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Big Data Mining and Analytics With MapReduce
High-velocity, valuable, and/or multi-variety data with volumes beyond the ability of commonly-used software to capture, manage, and process within a tolerable elapsed time. These Big Data necessitate new forms of processing to deliver high veracity (and low vulnerability) and to enable enhanced decision making, insight, knowledge discovery, and process optimization.
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Building an Analytics Culture to Boost a Data-Driven Entrepreneur's Business Model
A generic term that designates the massive volume of data that is generated by the increasing use of digital tools and information systems. The term big data is used when the amount of data that an organization has to manage reaches a critical volume that requires new technological approaches in terms of storage, processing, and usage. Volume, velocity, and variety are usually the three criteria used to qualify a database as “big data.”
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New Perspectives on Sustainable Healthcare Delivery Through Web of Things
The term is used for large and/or complex sets of structured or unstructured data that cannot be processed in traditional ways. As a concept, big data is defined around the four V’s: volume (scale of data), velocity (analysis of streaming data), variety (different forms of data), and veracity (uncertainty of data).
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The Digital Transformation: Crafting Customer Engagement Strategies for Success
Large and complicated datasets that are difficult to handle, process, or analyze with conventional data processing methods are referred to as “big data. These datasets are characterized by their volume, velocity, variety, and often, their veracity.
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Marketing and Technologies Platforms in Smart F-Store
Very large sets of data that can only be stored, used, and analyzed with the help of technological tools and methods.
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Big Data Analytics for Business
The size, speed and sorts of data that exceed an organization’s traditional database capacity to access, integrate, store, and analyze for accurate and timely decision making.
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Anonymity and Pseudonymity in Data-Driven Science
A buzzword for huge amounts of data.
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Big Data Analytics in the Healthcare Industry
Is defined as the processing of massive amounts of data that collect over time that are difficult to analyze and handle using common database management tools. The data are very unstructured and analyzed for marketing trends in business as well as in the fields of manufacturing, medicine, and science.
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Spotted: Connecting People, Locations, and Real-World Events in a Cellular Network
An extremely large and complex data set of structured and unstructured data that cannot be processed using traditional data processing applications.
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Living inside the NET: The Primacy of Interactions and Processes
Broad term for data sets so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, and information privacy. The term often refers simply to the use of predictive analytics or other certain advanced methods to extract value from data, and seldom to a particular size of data set. Accuracy in big data may lead to more confident decision making.
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Big Data Analytics and IoT in Smart City Applications
Big data frequently refers to data sets with sizes away from the ability of frequently used software tools to confine, curate, administer, and process data contained by a supportable elapsed instance. Big data philosophy encompasses shapeless, semi-structured and prepared data, however the main focal point is on unstructured data.
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Big Data and Simulations for the Solution of Controversies in Small Businesses
The broad spectrum of data that have appeared throughout the development of the global information society.
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Artificial Neural Networks in Medicine: Recent Advances
Is a term referring to an extremely large collection of data, typically in the petabyte range or larger. The data is only considered “big” if it taxes current state-of-the-art computing capabilities.
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Awareness of Big Data Usage and Applications Among Librarians in Zimbabwe
Extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.
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Education in the Era of Industry 4.0: Qualifications, Challenges, and Opportunities
Data set that is extremely large in size and mostly unstructured in nature.
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Digital Art Events and Digital Art Museums
Big data is defined as a large amount of data sets that cannot be analyzed and managed with traditional data processing tools.
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Enhancing Airport Business Services Using Big Data Analytics
Data with at least one of the ten big characteristics, consisting of big volume, big velocity, big variety, big veracity, big intelligence, big analytics, big infrastructure, big service, big value, and big market.
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Abductive Strategies in Human Cognition and in Deep Learning Machines
Big data is a field that deals with methods for analyzing and methodically extracting information from, or otherwise dealing with data volumes that are too large or complicated for typical data-processing application software to handle.
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The Ambivalences of Smart Cities
Literally means a gigantic volume of data. Therefore, it is usually defined through five Vs: volume, velocity, variety, value, and veracity. Volume comes from the growing increase in data with which the Web is fed today. Velocity refers to the increased scalability of the computer that allows for faster processing of data. Variety accounts for the heterogeneity of data types. Value implies the concern with the reliability of the data and, finally, Veracity corresponds to the distinction that must be established between false and true data.
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Big Data for Digital Transformation of Public Services
Datasets characterized by Volume, Velocity, Variety, Variability, Veracity, Visualization, and Value.
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How Artificial Intelligence Can Enhance Predictive Maintenance in Smart Factories
It refers to the possibility of analyzing and systematically extracting information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.
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Business Intelligence
It is a popular term used to describe the exponential growth and availability of data, both structured and unstructured.
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The Incorporation of Big Data in Mathematical Training for the Fourth Industrial Revolution
Is a combination of structured, semistructured, and unstructured data collected by organizations that can be mined for information and used in machine learning projects, predictive modeling and other advanced analytics applications.
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Exploring the Possibilities of Artificial Intelligence and Big Data Techniques to Enhance Gamified Financial Services
It refers to the possibility of analyzing and systematically extracting information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.
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From the Data to the Statistical Analysis of Football: The Case of the Italian Serie A League
Term used to describe the set of technologies and methods of analysis of massive data. The term indicates the ability to analyze and relate a huge amount of data to discover the links between different phenomena and formulate predictions.
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Opportunities and Challenges of Big Data in Healthcare
Large amount of data, in many different formats, that flows rapidly in real time. This data should undergo some sort of analysis in order to extract useful information or knowledge.
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Review of the Role of the Internet of Things (IoT) on the Consumer Market: Focusing on Smart Tourism, Healthcare, and Retailing
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Big Brothers Are Seducing You: Consumerism, Surveillance, and the Agency of Consumers
Large and complex data sets which cannot be adequately processed using traditional data processing software or techniques. New techniques of statistics and machine learning have been developed to deal with big data.
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New Payment Models and Big Data Analytics
Gartner defines Big data as high-volume, high-velocity, and/or high-variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization (The importance of Big Data: A Definition. Douglas L).
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Big Data Analytics in Supply Chain Management
The evolving term that describes a large volume of structured, semi-structured and unstructured data that has the potential to be mined for information and used in machine learning projects and other advanced analytics applications.
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Enabling Technologies for IoT: Issues, Challenges, and Opportunities
The conventional techniques to store data are relational databases and sequential data processing. These techniques are efficient to handle and process limited data size. However, in today's scenario, there is very huge data been generated, through these conventional mechanisms, whereas fail to handle huge volumes of data. As a solution to this problem, big data mechanisms and tools are effective to handle these huge volumes of data sets.
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Digital Transformation Stemming From a Business Assessment of Construction Industry 4.0
The big data is data that contains greater variety, arriving in increasing volumes and with more velocity.
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Oracle 19c's Multitenant Container Architecture and Big Data
Data that contains greater variety, arriving in increasing volumes and with high velocity.
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BIG Data: An Enabler in Developing Business Models in Cloud Computing Environments
The capability to manage a huge volume of disparate data, at the right speed and within the right time frame, to allow real time analysis and reaction.
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Internet Privacy
A data set this is too large for “standard” software programs, and is generally used to identify large trends, and predict behaviors and outcomes.
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Emerging EdTechs Amidst the COVID-19 Pandemic: Cases in Higher Education Institutions
Large data sets that are analysed using a computer to reveal patterns, trends, and relations pertaining to human behaviour and interactions.
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First of All, Understand Data Analytics Context and Changes
A generic term that designates the massive volume of data that is generated by the increasing use of digital tools and information systems. The term big data is used when the amount of data that an organization has to manage reaches a critical volume that requires new technological approaches in terms of storage, processing, and usage. Volume, velocity, and variety are usually the three criteria used to qualify a database as “big data.”
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Big Data Analytics for Intrusion Detection: An Overview
Traditional technologies of data processing, have difficulties to handle in tolerable time a large dataset.
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Artificial Intelligence, Big Data, and Machine Learning in Industry 4.0
An exponentially increasing volume of heterogeneous data which is differentiated from traditional data based on its volume, variety, veracity, velocity and value.
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Blockchain Technology in the Automotive Industry: Use Cases and Statistical Evaluation
Big data refers to large amounts of heterogeneous data that cannot be easily processed using conventional database techniques. Big data characteristics include volume, variety, and velocity of data. This data is generated by many sources including smart sensors, smartwatches, wristbands, medical equipment/devices, tablets, mobile phones, web usage records, social media, and simulation.
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Research Trends in Information Systems From the Management Discipline Based on Co-Occurrence Analysis
Refers to large data sets. The definition of the term may also include the specific tools for their processing and structured or unstructured analysis that facilitate business decision making by revealing new patterns, associations, and trends.
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Embracing Technological Advancements: A Futuristic Approach to Hospitality Management
Big data is large, complex, and diverse sets of data that keep on growing exponentially over time. Traditional data management systems are not compatible with storing, process, and analysing big data due to their large volume and complexity.
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Data Science and Distributed Intelligence
A collection of models, techniques and algorithms that aim at representing, managing, querying and mining large-scale amounts of data (mainly semi-structured data) in distributed environments (e.g., Clouds).
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Generating Big Data in (Micro)Economics
Unconventionally large data streams from many sources to a bunch of (not necessarily known) recipients.
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Emerging Tools and Technologies in Data Science
Big data – a simple word turned into a technical jargon now-a-days to many common people because of its extensive use in the computing world with both its implicit and explicit meanings. The connotation of the term does not mean only the size of the raw facts the concerned people have to deal with, it also gives an impression about the scope and importance of those facts, budget, tools, technologies, and expertise to process those unstructured facts, and an apprehension of the utility of the information to be derived from those raw facts.
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Big Data, Who Are You?
A generic term that designates the massive volume of data that is generated by the increasing use of digital tools and information systems. The term big data is used when the amount of data that an organization has to manage reaches a critical volume that requires new technological approaches in terms of storage, processing, and usage. Volume, velocity, and variety are usually the three criteria used to qualify a database as “big data.”
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E-Court: The Future of Commercial Dispute and the Quality of Judicial Processes in Indonesia
Very large sets of data that are produced by people using the internet, and that can only be stored, understood, and used with the help of special tools and methods.
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Supply Chain Analytics in the Era of Big Data
A collection of data sets which are too large and complex to process using traditional methods or techniques.
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Smart Management for Digital Transformation in China
A large-scale data collection that greatly exceeds the capabilities of traditional database software tools in terms of acquisition, storage, management, and analysis.
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Segmenting Big Data Time Series Stream Data
Big data usually includes data sets with sizes beyond the ability of commonly-used software tools to capture, curate, manage, and process the data within a tolerable elapsed time.
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The Growth of Cyberbullying at Workplace After COVID-19: The Problems of New Forms of Communication
Data sets or combinations of datasets whose size (volume), complexity (variability), and speed of growth (velocity) make it difficult to capture, manage, process, or analyze them using conventional technologies and tools, such as relational databases and conventional statistics or visualization packages, within the time necessary to make them useful.
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Intelligent Management and Efficient Operation of Big Data
The term that represents data sets that are extremely large to handle through traditional methods. Big data represents information that has such a high volume, velocity, variety, variability, veracity and complexity that require specific mechanisms to produce real value from it in a timely way.
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Applying a Methodology in Data Transmission of Discrete Events From the Perspective of Cyber-Physical Systems Environments
It is the technology that uses solutions based on algorithms that capture and cross-data organized, which allows the storage and retrieval of data of various formats at a high scale.
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Harnessing the Power of Artificial Intelligence in Law Enforcement: A Comprehensive Review of Opportunities and Ethical Challenges
A term for the amount of data that has emerged in recent years and refers to data sets of such a size that they are difficult to process with traditional methods. (sw. big data)
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Assessment in Academic Libraries
Digital data whose massive scale and complex, unstructured content defy analysis with conventional tools, but which can increasingly be put to useful purposes through emerging data processing technologies.
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Digital Transformation in Banks of Different Sizes: Evidence From the Polish Banking Sector
The use of very large and complex data sets for business analytics. Big Data sets are usually defined by their size (exceeding the capability of common statistical software and metods), complexity (as they can contain data of multiple types, including numbers, text, image, etc.), velocity (as these sets can be collected and analyzed in a continuous fashion, e.g. in case of data capturing the patterns of use of an application by clients).
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Content Bubbles: How Platforms Filter What We See
A set of data whose size makes it difficult for it to be recorded, managed and analysed by using conventional tools.
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Digital Humanities Strategy
Large collections of either structured, semi-structured, or unstructured data that is processed by computer applications.
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Cyber Security in Health: Standard Protocols for IoT and Supervisory Control Systems
Extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.
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Price Strategies in a Big Data World
Voluminous amount of structured, semi-structured and unstructured data that has potential to be mined for information.
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Future Networked Healthcare Systems: A Review and Case Study
It refers to the emerging technologies that are designed to extract value from data having four Vs characteristics; volume, variety, velocity and veracity. Big data is set to affect the future network traffic and hence the network architectures.
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Big Data Analytics for Search Engine Optimization in Intelligent Business
Big data is a term that refers to massive, various amounts of data that are accumulating at an exponential rate.
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Emerging Auditing Perspectives in the Age of the Fourth Industrial Revolution
The whole of the processable form of high-volume data obtained from different sources.
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Big Data and Digital Tools Applied to the Teaching: Learning in Graduate Programs in Mexico
Is a recurring term when talking about technology and digitalization, its involvement in many areas of life begins to be relevant. Big Data refers to the management and analysis of huge volumes of data, which due to the magnitude of the information, exceed the capacity of data processing and should be treated in a special way.
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The Nature of Intelligent Analytics
Is data with at least one of the ten big characteristics consisting of big volume, big velocity, big variety, big veracity, big intelligence, big analytics, big infrastructure, big service, big value, and big market.
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