Towards a Low Cost ETL System

Santos, Vasco; Silva, Rui; Belo, Orlando

doi:10.5121/ijdms.2014.6205

Cited by 4 publications

(5 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…OLAP is such a well-recognized and well-respected methodology for “Big Data” research in BI systems [ 36 ]. However, while BI, OLAP, and data warehouse are powerful tools for coping with vast volumes of data and a vast variety of operations, they also provide a challenge owing to the considerable cost, space, and computing resources necessary [ 37 – 40 ]. The authors introduced new data mining techniques in these researches [ 41 – 43 ].…”

Section: Related Workmentioning

confidence: 99%

Understanding the User-Generated Geographic Information by Utilizing Big Data Analytics for Health Care

Ullah

Hameed

Rizvi

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

There are two main ways to achieve an active lifestyle, the first is to make an effort to exercise and second is to have the activity as part of your daily routine. The study’s major purpose is to examine the influence of various kinds of physical engagements on density dispersion of participants in Shanghai, China, and even prototype check-in data from a Location-Based Social Network (LBSN) utilizing a mix of spatial, temporal, and visualization methodologies. This paper evaluates Weibo used for big data evaluation and its dependability in some types rather than physically collected proofs by investigating the relationship between time, class, place, frequency, and place of check-in built on geographic features and related consequences. Kernel density estimation has been used for geographical assessment. Physical activities and frequency allocation are formed as a result of hour-to-day consumption habits. Our observations are based on customer check-in activities in physical venues such as gyms, parks, and playing fields, the prevalence of check-ins, peak times for visiting fun parks, and gender disparities, and we applied relative difference formulation to reveal the gender difference in a much better way. The purpose of this research is to investigate the influence of physical activity and health-related standard of living on well-being in a selection of Shanghai inhabitants.

show abstract

Section: Related Workmentioning

confidence: 99%

Understanding the User-Generated Geographic Information by Utilizing Big Data Analytics for Health Care

Ullah

Hameed

Rizvi

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

“…OLAP is one of the most well-known and renowned methodologies for "big data" research in BI systems [33]. However, BI, data warehouse, and OLAP are potent tools for dealing with large amounts of data and a wide range of activities, additionally posing a difficulty due to the high cost, storage, and processing resources required [34]. As it has been utilized and is developing rapidly in practically every area globally, online social networks have proven to be the most momentous source of "big data" to study individual's behaviour.…”

Section: Related Workmentioning

confidence: 99%

Spatiotemporal Analysis of Residents in Shanghai by Utilizing Chinese Microblog Weibo Data

Hou

Liu

Uddin

et al. 2021

Mobile Information Systems

View full text Add to dashboard Cite

Mobile applications are really important nowadays due to providing the accurate check-in data for research. The primary goal of the study is to look into the impact of several forms of entertainment activities on the density dispersal of occupants in Shanghai, China, as well as prototypical check-in data from a location-based social network using a combination of temporal, spatial, and visualization techniques and categories of visitors’ check-ins. This article explores Weibo for big data assessment and its reliability in a variety of categories rather than physically obtained information by examining the link between time, frequency, place, class, and place of check-in based on geographic attributes and related implications. The data for this study came from Weibo, a popular Chinese microblog. It was preprocessed to extract the most important and associated results elements, then converted to geographical information systems format, appraised, and finally displayed using graphs, tables, and heat maps. For data significance, a linear regression model was used, and, for spatial analysis, kernel density estimation was utilized. As per results of hours-to-day usage patterns, enjoyment activities and frequency distribution are produced. Our findings are based on the check-in behaviour of users at amusement locations, the density of check-ins, rush periods for visiting amusement locations, and gender differences. Our data provide light on different elements of human behaviour patterns, the importance of entertainment venues, and their impact in Shanghai. So it can be used in pattern recognition, endorsement structures, and additional multimedia content for these collections.

show abstract

“…OLAP is recognized as one of the most dominant and well-known tools for "Big Data" analysis for decision support in BI systems [44]. BI, Data Warehouse and OLAP are very powerful tools dealing with vast amount of data and various operations, and therefore are also a challenge due to the requirement of massive cost, storage and computational resources [45].…”

Section: Literature Reviewmentioning

confidence: 99%

A Study of User Activity Patterns and the Effect of Venue Types on City Dynamics Using Location-Based Social Network Data

Khan

Wan

et al. 2020

IJGI

View full text Add to dashboard Cite

The main purpose of this research is to study the effect of various types of venues on the density distribution of residents and model check-in data from a Location-Based Social Network for the city of Shanghai, China by using combination of multiple temporal, spatial and visualization techniques by classifying users’ check-ins into different venue categories. This article investigates the use of Weibo for big data analysis and its efficiency in various categories instead of manually collected datasets, by exploring the relation between time, frequency, place and category of check-in based on location characteristics and their contributions. The data used in this research was acquired from a famous Chinese microblogs called Weibo, which was preprocessed to get the most significant and relevant attributes for the current study and transformed into Geographical Information Systems format, analyzed and, finally, presented with the help of graphs, tables and heat maps. The Kernel Density Estimation was used for spatial analysis. The venue categorization was based on nature of the physical locations within the city by comparing the name of venue extracted from Weibo dataset with the function such as education for schools or shopping for malls and so on. The results of usage patterns from hours to days, venue categories and frequency distribution into these categories as well as the density of check-in within the Shanghai and contribution of each venue category in its diversity are thoroughly demonstrated, uncovering interesting spatio-temporal patterns including frequency and density of users from different venues at different time intervals, and significance of using geo-data from Weibo to study human behavior in variety of studies like education, tourism and city dynamics based on location-based social networks. Our findings uncover various aspects of activity patterns in human behavior, the significance of venue classes and its effects in Shanghai, which can be applied in pattern analysis, recommendation systems and other interactive applications for these classes.

show abstract

Towards a Low Cost ETL System

Cited by 4 publications

References 30 publications

Understanding the User-Generated Geographic Information by Utilizing Big Data Analytics for Health Care

Understanding the User-Generated Geographic Information by Utilizing Big Data Analytics for Health Care

Spatiotemporal Analysis of Residents in Shanghai by Utilizing Chinese Microblog Weibo Data

A Study of User Activity Patterns and the Effect of Venue Types on City Dynamics Using Location-Based Social Network Data

Contact Info

Product

Resources

About