scholarly journals A Seismological and Geophysical Database of Kos Island: 10 Years of Digital Records

Earth ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 920-932
Author(s):  
Alexandra Moshou
Keyword(s):  
Big Data ◽  
Seismic Hazard ◽  
Selection Criteria ◽  
Tide Gauge ◽  
Broadband Seismograms ◽  
New Research

A ten-year complete seismological database is evaluated in the present work. These data are provided for events with magnitude ML ≥ 1.0, which have occurred in Eastern Greece and, more specifically, in Kos Island. Several selection criteria are applied and, hence, a catalog of the seismological records is compiled. Detailed big data (seismological, tide gauge, geodetic stations, accelerometers, etc.) of this region are used and processed in this work. The database consists of approximately 35,000 three-component broadband seismograms from 1198 digitally recorded events. It covers the last ten years of measurements, including records from the 20 July 2017, ML 6.2, Kos Island, Greece event. The seismological communities can either use this database to conduct new research or improve already existing seismic hazard studies in the region.

Insights into seismic hazard from big data analysis of ground motion simulations

2019 ◽  
Vol 9 (1) ◽  
pp. 01-12 ◽  
Author(s):  
Kristy F. Tiampo ◽  
Javad Kazemian ◽  
Hadi Ghofrani ◽  
Yelena Kropivnitskaya ◽  
Gero Michel
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Seismic Hazard ◽  
Ground Motion ◽  
Big Data Analysis ◽  
Ground Motion Simulations

THE RELATIONSHIP OF SOCIOTECHNICAL AND TECHNOLOGICAL ASPECTS OF THE INTRODUCTION AND APPLICATION OF BUSINESS INTELLIGENCE SYSTEMS

2021 ◽  
Vol 5 (12) ◽  
pp. 30-35
Author(s):  
Edward N. Ozhiganov ◽  
◽  
Alexander A. Chursin ◽  
Alexey D. Linkov ◽  
◽  
...  
Keyword(s):  
Big Data ◽  
Business Intelligence ◽  
New Technologies ◽  
Business Analytics ◽  
Scientific Publications ◽  
Business Decisions ◽  
Business Decision ◽  
Business Intelligence Systems ◽  
Demand Fluctuations ◽  
New Research

This article describes a relation between sociotechnical and technological factors involved in launching and implementing Business Intelligence systems. Advanced BI systems include business analytics, data mining, data visualization, data tools and infrastructure, and advanced IT solutions to support business decisions based on big data. Various industries and businesses handle large amounts of data to adapt to changing markets and demand fluctuations, push new technologies, and repair ineffective strategies, etc. With an upsurge in data sizes, more and more new research papers are published today to describe BI implemen-tation, use and results. However, today most studies and scientific publications focus on Business Intelligence technological challenges, while sociotechnical aspects – that is processes involved in business decision mak-ing based on big data – are studied in much rarer cases.

scholarly journals The Rise of Big Data Science: A Survey of Techniques, Methods and Approaches in the Field of Natural Language Processing and Network Theory

2018 ◽  
Vol 2 (3) ◽  
pp. 22 ◽  
Author(s):  
Jeffrey Ray ◽  
Olayinka Johnny ◽  
Marcello Trovati ◽  
Stelios Sotiriadis ◽  
Nik Bessis
Keyword(s):  
Big Data ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Network Theory ◽  
Data Science ◽  
Theoretical Foundation ◽  
Scientific Field ◽  
Research Challenges ◽  
New Research

The continuous creation of data has posed new research challenges due to its complexity, diversity and volume. Consequently, Big Data has increasingly become a fully recognised scientific field. This article provides an overview of the current research efforts in Big Data science, with particular emphasis on its applications, as well as theoretical foundation.

scholarly journals Use cases and challenges in telecom big data analytics

2016 ◽  
Vol 5 ◽  
Author(s):  
Chung-Min Chen
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Driving Forces ◽  
Big Data Analytics ◽  
Use Cases ◽  
Telecommunication Industry ◽  
New Research

This paper examines the driving forces of big data analytics in the telecom domain and the benefits it offers. We provide example use cases of big data analytics and the associated challenges, with the hope to inspire new research ideas that can eventually benefit the practice of the telecommunication industry.

scholarly journals Pricing Strategies of a Three-Stage Supply Chain: A New Research in the Big Data Era

2017 ◽  
Vol 2017 ◽  
pp. 1-16
Author(s):  
Pan Liu
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Stackelberg Game ◽  
Chain Model ◽  
Pricing Strategies ◽  
Supply Chain Model ◽  
Investment Cost ◽  
New Research ◽  
New Situation ◽  
Big Data Technology

In the Big Data era, Data Company as the Big Data information (BDI) supplier should be included in a supply chain. In the new situation, to research the pricing strategies of supply chain, a three-stage supply chain with one manufacturer, one retailer, and one Data Company was chosen. Meanwhile, considering the manufacturer contained the internal and external BDI, four benefit models about BDI investment were proposed and analyzed in both decentralized and centralized supply chain using Stackelberg game. Meanwhile, the optimal retail price and benefits in the four models were compared. Findings are as follows. (1) The industry cost improvement coefficient, the internal BDI investment cost of the manufacturer, and the added cost of the Data Company on using Big Data technology have different relationships with the optimal prices of supply chain members in different models. (2) In the retailer-dominated supply chain model, the optimal benefits of the retailer and the manufacturer are the same, and the optimal benefits of the Data Company are biggest in all the members.

From Business Intelligence to Big Data

2021 ◽  
pp. 44-62
Author(s):  
Mouhib Alnoukari
Keyword(s):  
Big Data ◽  
Organizational Performance ◽  
Business Intelligence ◽  
Corporate Strategy ◽  
Big Data Analytics ◽  
Organizational Capability ◽  
Strategy Transformation ◽  
Executive Managers ◽  
New Research ◽  
Research Challenge

Boundaries between business intelligence (BI), big data (BD), and big data analytics (BDA) are often unclear and ambiguous for companies. BD is a new research challenge; it is becoming a subject of growing importance. Notably, BD was one of the big buzzwords during the last decade. BDA can help executive managers to plan an organization's short-term and long-term goals. Furthermore, BI is considered as a kind of decision support system (DSS) that can help organizations achieving their goals, creating corporate value and improving organizational performance. This chapter provides a comprehensive view about the interrelationships between BI, BD, and BDA. Moreover, the chapter highlights the power of analytics that make them considered as one of the highly impact's organizational capability. Additionally, the chapter can help executive managers to decide the way to integrate BD initiatives as a tool, or as an industry, or as a corporate strategy transformation.

scholarly journals Big Data in Finance

2021 ◽  
Author(s):  
Itay Goldstein ◽  
Chester S Spatt ◽  
Mao Ye
Keyword(s):  
Big Data ◽  
Asset Pricing ◽  
Complex Structure ◽  
Future Research ◽  
Special Issue ◽  
Research Directions ◽  
Finance Industry ◽  
Large Size ◽  
Future Research Directions ◽  
New Research

Abstract Big data is revolutionizing the finance industry and has the potential to significantly shape future research in finance. This special issue contains papers following the 2019 NBER-RFS Conference on Big Data. In this introduction to the special issue, we define the “big data” phenomenon as a combination of three features: large size, high dimension, and complex structure. Using the papers in the special issue, we discuss how new research builds on these features to push the frontier on fundamental questions across areas in finance—including corporate finance, market microstructure, and asset pricing. Finally, we offer some thoughts for future research directions.

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