The Impact of Merged Data in Big Data Platform: A Case Study

Author(s):  
Oded Koren ◽  
Nir Perel ◽  
Michal Koren
Keyword(s):  
Big Data ◽  
2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alexander Schlegel ◽  
Hendrik Sebastian Birkel ◽  
Evi Hartmann

PurposeThe purpose of this study is to investigate how big data analytics capabilities (BDAC) enable the implementation of integrated business planning (IBP) – the advanced form of sales and operations planning (S&OP) – by counteracting the increasing information processing requirements.Design/methodology/approachThe research model is grounded in the organizational information processing theory (OIPT). An embedded single case study on a multinational agrochemical company with multiple geographically distinguished sub-units of analysis was conducted. Data were collected in workshops, semistructured interviews as well as direct observations and enriched by secondary data from internal company sources as well as publicly available sources.FindingsThe results show the relevancy of establishing BDAC within an organization to apply IBP by providing empirical evidence of BDA solutions in S&OP. The study highlights how BDAC increase an organization's information processing capacity and consequently enable efficient and effective S&OP. Practical guidance toward the development of tangible, human and intangible BDAC in a particular sequence is given.Originality/valueThis study is the first theoretically grounded, empirical investigation of S&OP implementation journeys under consideration of the impact of BDAC.


2021 ◽  
Vol 10 (10) ◽  
pp. 678
Author(s):  
Yu Gao ◽  
Dongqi Sun ◽  
Jingxiang Zhang

The global outbreak of the COVID-19 epidemic has caused a considerable impact on humans, which expresses the urgency and importance of studying its impacts. Previous studies either frequently use aggregated research methods of statistic data or stay during COVID-19. The afterward impacts of COVID-19 on human behaviors need to be explored further. This article carries out a non-aggregated study methodology in human geography based on big data from social media comments and takes Nanjing, China, as the research case to explore the afterward impact of the COVID-19 epidemic on the spatial behavior of urban tourists. Precisely, we propose the methodology covers two main aspects regarding travel contact trajectory and spatial trajectory. In contact trajectory, we explore three indicators—Connection Strength, Degree Centrality, and Betweenness Centrality—of the collected attractions. Then, in spatial trajectory, we input the results from contact trajectory into ArcGIS by using the Orientation–Destination Model and Standard Deviation Ellipse to explore the influences on the spatial pattern. By setting up comparative groups for the three periods of before, during, and after the COVID-19 in Nanjing, this study found that, in the post-epidemic era, (1) the spatial behavior of urban tourists showed a state of overall contraction; (2) the objects of contraction changed from urban architectural attractions to urban natural attractions; (3) the form of contraction presents concentric circles with the central city (Old City of Nanjing) as the core; (4) the direction of contraction heads to the large-scale natural landscape in the central city, which highlights the importance of green open spaces in the post-epidemic era.


Author(s):  
H. Li ◽  
W. Huang ◽  
Z. Zha ◽  
J. Yang

Abstract. With the wide application of Big Data, Artificial Intelligence and Internet of Things in geographic information technology and industry, geospatial big data arises at the historic moment. In addition to the traditional "5V" characteristics of big data, which are Volume, Velocity, Variety, Veracity and Valuable, geospatial big data also has the characteristics of "Location Attribute". At present, the study of geospatial big data are mainly concentrated in: knowledge mining and discovery of geospatial data, Spatiotemporal big data mining, the impact of geospatial big data on visualization, social perception and smart city, geospatial big data services for government decision-making support four aspects. Based on the connotation and extension of geospatial big data, this paper comprehensively defines geospatial big data comprehensively. The application of geospatial big data in location visualization, industrial thematic geographic information comprehensive service and geographic data science and knowledge service is introduced in detail. Furthermore, the key technologies and design indicators of the National Geospatial Big Data Platform are elaborated from the perspectives of infrastructure, functional requirements and non-functional requirements, and the design and application of the National Geospatial Public Service Big Data Platform are illustrated. The challenges and opportunities of geospatial big data are discussed from the perspectives of open resource sharing, management decision support and data security. Finally, the development trend and direction of geospatial big data are summarized and prospected, so as to build a high-quality geospatial big data platform and play a greater role in social public application services and administrative management decision-making.


2020 ◽  
Vol 5 (3) ◽  

This paper is based on big data collected from a period of 1,420daysfrom 6/1/2015 to 4/21/2019 with a total of 4,260 data, including highest ambient temperature (weather) of each day in degree Fahrenheit (°F), fasting plasma glucose (FPG) and postprandial plasma glucose (PPG) in mg/dL. The dataset is provided by the author, who uses his own type 2 diabetes metabolic conditions control, as a case study via the “math-physical medicine” approach of a non-traditional methodology in medical research.


2020 ◽  
Vol 214 ◽  
pp. 01004
Author(s):  
Wang Yang

”Big data” is the product of the integration of the highly developed Internet innovation function and various economic fields in today’s society. The development of “big data” is bound to bring significant changes in the economic development of today’s society. Taking HUA WEI technologies co., LTD., financial aspects based on the development of big data, found big data technology in the application process of the impact of the financial accounting, this era of big data work flow for the company in China, the impact of financial decision-making and financial personnel, and the company response to this phenomenon and make a change, and to analyze its causes and solutions. This electronic document is a “live” template. The various components of your paper [title, text, heads, etc.] are already defined on the style sheet, as illustrated by the portions given in this document.


Sign in / Sign up

Export Citation Format

Share Document