scholarly journals Data Science and Big Data Technologies Role in the Digital Economy

TEM Journal ◽  
2020 ◽  
pp. 756-762
Author(s):  
Sergey V. Novikov
Keyword(s):  
Big Data ◽  
Data Science ◽  
Predictive Analytics ◽  
Liquid Product ◽  
Digital Economy ◽  
Retail Trade ◽  
Necessary Condition ◽  
Manufacturing Companies ◽  
Big Data Technology

This article explores the role of Data Science and Big Data technology in the modern digital economy. The author states that large and medium companies from retail trade and service sector show increased interest in using them. These technologies are actively used by banks, mobile operators and large manufacturing companies to analyze data on equipment failures and to reduce downtime, which allows reducing costs. The role of Big Data technology is to be a liquid product and a necessary condition to increase the profitability of enterprises through personalized customer service and predictive analytics. For today's Russian digital economy, it is very important to legalize a single definition of Big Data and to achieve the emergence of special data exchanges.

scholarly journals The Role of Big Data and Predictive Analytics in Retailing

2017 ◽  
Vol 93 (1) ◽  
pp. 79-95 ◽  
Author(s):  
Eric T. Bradlow ◽  
Manish Gangwar ◽  
Praveen Kopalle ◽  
Sudhir Voleti
Keyword(s):  
Big Data ◽  
Predictive Analytics

Big-Data-Based Techniques for Predictive Intelligence

2019 ◽  
pp. 1-18
Author(s):  
Dharmpal Singh ◽  
Madhusmita Mishra ◽  
Sudipta Sahana
Keyword(s):  
Big Data ◽  
Competitive Advantage ◽  
Predictive Analytics ◽  
Unstructured Data ◽  
Security Issue ◽  
Operational Costs ◽  
Big Data Technologies ◽  
Ending Process ◽  
Big Data Technology

Big-data-analyzed finding patterns derive meaning and make decisions on data to produce responses to the world with intelligence. It is an emerging area used in business intelligence (BI) for competitive advantage to analyze the structured, semi-structured, and unstructured data stored in different formats. As the big data technology continues to evolve, businesses are turning to predictive intelligence to deepen the engagement to customers with optimization in processes to reduce the operational costs. Predictive intelligence uses sets of advanced technologies that enable organizations to use data stored in real time that move from a historical and descriptive view to a forward-looking perspective of data. The comparison and other security issue of this technology is covered in this book chapter. The combination of big data technology and predictive analytics is sometimes referred to as a never-ending process and has the possibility to deliver significant competitive advantage. This chapter provides an extensive review of literature on big data technologies and its usage in the predictive intelligence.

Role of Urban Big Data in Travel Behavior Research

2020 ◽  
pp. 036119812097502
Author(s):  
Chihuangji Wang ◽  
Daniel Baldwin Hess
Keyword(s):  
Big Data ◽  
Survey Data ◽  
Travel Behavior ◽  
Data Science ◽  
Location Based Service ◽  
Labor Costs ◽  
Public And Private ◽  
Public And Private Sector ◽  
Data Analytic

Understanding urban travel behavior (TB) is critical for advancing urban transportation planning practice and scholarship; however, traditional survey data is expensive (because of labor costs) and error-prone. With advances in data collection techniques and data analytic approaches, urban big data (UBD) is currently generated at an unprecedented scale in relation to volume, variety, and speed, producing new possibilities for applying UBD for TB research. A review of more than 50 scholarly articles confirms the remarkable and expanding role of UBD in TB research and its advantages over traditional survey data. Using this body of published work, a typology is developed of four key types of UBD—social media, GPS log, mobile phone/location-based service, and smart card—focusing on the features and applications of each type in the context of TB research. This paper discusses in significant detail the opportunities and challenges in the use of UBD from three perspectives: conceptual, methodological, and political. The paper concludes with recommendations for researchers to develop data science knowledge and programming skills for analysis of UBD, for public and private sector agencies to cooperate on the collection and sharing of UBD, and for legislators to enforce data security and confidentiality. UBD offers both researchers and practitioners opportunities to capture urban phenomena and deepen knowledge about the TB of individuals.

Role of big data and predictive analytics

2016 ◽  
Vol 2 (4) ◽  
pp. 307
Author(s):  
Sneha Kumari ◽  
Yogesh Patil ◽  
Shirish Jeble
Keyword(s):  
Big Data ◽  
Predictive Analytics

scholarly journals Public Management Innovation in the Age of Big Data

2019 ◽  
Vol 2 (4) ◽  
Author(s):  
Yichu Wang
Keyword(s):  
Big Data ◽  
Public Management ◽  
Great Influence ◽  
Management Innovation ◽  
Daily Lives ◽  
The Public ◽  
Internet Age ◽  
The People ◽  
Big Data Technology

In the Internet age, computer technology and data analysis technology have been applied to the daily lives and work of the people. Big data technology has brought great influence to public management, providing efficient and convenient public services and improving the ability to cope with public opinion crises [1]. However, in the actual public management process, there are widespread problems such as single practice and poor data openness. Based on this, the article expounds the relevant content of big data, introduces the role of big data in public management, and studies the public management innovation in the age of big data.

scholarly journals DATA SCIENCE, BIG DATA, AND PREDICTIVE ANALYTICS: A PLATFORM FOR CYBERSPACE SECURITY INTELLIGENCE

2017 ◽  
Vol 7 (2) ◽  
Author(s):  
Dicky R. M. Nainggolan
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Cyber Security ◽  
High Speed ◽  
Data Science ◽  
Predictive Analytics ◽  
Cyber Attacks ◽  
Artificial Intelligence Technology ◽  
Science Methodology ◽  
Cyberspace Security

<p><em><strong>Abstract</strong> – Data are the prominent elements in scientific researches and approaches. Data Science methodology is used to select and to prepare enormous numbers of data for further processing and analysing. Big Data technology collects vast amount of data from many sources in order to exploit the information and to visualise trend or to discover a certain phenomenon in the past, present, or in the future at high speed processing capability. Predictive analytics provides in-depth analytical insights and the emerging of machine learning brings the data analytics to a higher level by processing raw data with artificial intelligence technology. Predictive analytics and machine learning produce visual reports for decision makers and stake-holders. Regarding cyberspace security, big data promises the opportunities in order to prevent and to detect any advanced cyber-attacks by using internal and external security data.</em></p><p><br /><em><strong>Keywords</strong>: Big Data, Cyber Security, Data Science, Intelligence, Predictive Analytics</em></p><p><br /><em><strong>Abstrak</strong> – Data merupakan unsur terpenting dalam setiap penelitian dan pendekatan ilmiah. Metodologi sains data digunakan untuk memilah, memilih dan mempersiapkan sejumlah data untuk diproses dan dianalisis. Teknologi big data mampu mengumpulkan data dengan sangat banyak dari berbagai sumber dengan tujuan untuk mendapatkan informasi dengan visualisasi tren atau menyingkapkan pengetahuan dari suatu peristiwa yang terjadi baik dimasa lalu, sekarang, maupun akan datang dengan kecepatan pemrosesan data sangat tinggi. Analisis prediktif memberikan wawasan analisis lebih dalam dan kemunculan machine learning membawa analisis data ke tingkat yang lebih tinggi dengan bantuan teknologi kecerdasan buatan dalam tahap pemrosesan data mentah. Analisis prediktif dan machine learning menghasilkan laporan berbentuk visual untuk pengambil keputusan dan pemangku kepentingan. Berkenaan dengan keamanan siber, big data menjanjikan kesempatan dalam rangka untuk mencegah dan mendeteksi setiap serangan canggih siber dengan memanfaatkan data keamanan internal dan eksternal.</em></p><p><br /><strong>Kata Kunci</strong>: Analisis Prediktif, Big Data, Intelijen, Keamanan Siber, Sains Data</p>

scholarly journals SAINS DATA, BIG DATA, DAN ANALISIS PREDIKTIF: SEBUAH LANDASAN UNTUK KECERDASAN KEAMANAN SIBER

2017 ◽  
Vol 7 (2) ◽  
Author(s):  
Dicky R. M. Nainggolan
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Cyber Security ◽  
High Speed ◽  
Data Science ◽  
Predictive Analytics ◽  
Cyber Attacks ◽  
Artificial Intelligence Technology ◽  
Science Methodology ◽  
Many Sources

<p><strong>Abstrak</strong> – Data merupakan unsur terpenting dalam setiap penelitian dan pendekatan ilmiah. Metodologi sains data digunakan untuk memilah, memilih dan mempersiapkan sejumlah data untuk diproses dan dianalisis. Teknologi big data mampu mengumpulkan data dengan sangat banyak dari berbagai sumber dengan tujuan untuk mendapatkan informasi dengan visualisasi tren atau menyingkapkan pengetahuan dari suatu peristiwa yang terjadi baik dimasa lalu, sekarang, maupun akan datang dengan kecepatan pemrosesan data sangat tinggi. Analisis prediktif memberikan wawasan analisis lebih dalam dan kemunculan machine learning membawa analisis data ke tingkat yang lebih tinggi dengan bantuan teknologi kecerdasan buatan dalam tahap pemrosesan data mentah. Analisis prediktif dan machine learning menghasilkan laporan berbentuk visual untuk pengambil keputusan dan pemangku kepentingan. Berkenaan dengan keamanan siber, big data menjanjikan kesempatan dalam rangka untuk mencegah dan mendeteksi setiap serangan canggih siber dengan memanfaatkan data keamanan internal dan eksternal.</p><p><br /><strong>Kata Kunci</strong>: analisis prediktif, big data, intelijen, keamanan siber, sains data</p><p><strong><em>Abstract</em> </strong>– Data are the prominent elements in scientific researches and approaches. Data Science methodology is used to select and to prepare enormous numbers of data for further processing and analysing. Big Data technology collects vast amount of data from many sources in order to exploit the information and to visualise trend or to discover a certain phenomenon in the past, present, or in the future at high speed processing capability. Predictive analytics provides in-depth analytical insights and the emerging of machine learning brings the data analytics to a higher level by processing raw data with artificial intelligence technology. Predictive analytics and machine learning produce visual reports for decision makers and stake-holders. Regarding cyberspace security, big data promises the opportunities in order to prevent and to detect any advanced cyber-attacks by using internal and external security data.</p><p><br /><strong><em>Keywords</em></strong>: big data, cyber security, data science, intelligence, predictive analytics</p>

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