Experimental Characteristics Study of Data Storage Formats for Data Marts Development within Data Lakes

Belov, V.; Kosenkov, Alexander; Nikulchev, Evgeny

doi:10.3390/app11188651

Cited by 5 publications

(3 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Selection of the process: The data mart that is built first must be the one that can be transferred in a timely manner and address all important business queries. Data mart is a database containing data that only describes segments of corporate operations [16].…”

Section: Nine-step Methodologymentioning

confidence: 99%

Modelling of Data Warehouse With Making the Trend to Make Decision in Company Xyz

Simatupang

Fergina

Ozsut

2022

IJEAT

View full text Add to dashboard Cite

The goals of the thesis were to modellig a data warehouse which was loaded from the operational database PT. XYZ, to analyze data warehouse with Tableau Software to know the trends of activity Trouble ticket, and to create reports and dashboards to facilitate PT. XYZ in viewing the trends. Data were compiled by observation to PT. XYZ from reporting team. Data were analyzed using software tableau. The results obtained were the trend of activity trouble ticket more than two hundred thousand data in sixteen weeks or four month in 2017. It can be concluded that developed data warehouse can be used to analyze in gaining information about the trends of activity trouble ticket and help to make a decision.

show abstract

Section: Nine-step Methodologymentioning

confidence: 99%

Modelling of Data Warehouse With Making the Trend to Make Decision in Company Xyz

Simatupang

Fergina

Ozsut

2022

IJEAT

View full text Add to dashboard Cite

show abstract

“…Other studies have explored the advantages of Hadoop in storing and searching proteomic datasets [14], as well as storing largescale genomic data in FASTA/Q files [15]. In addition, research has been conducted to explore the use of Hadoop in connecting painting resources with a storage-and-retrieval system [16] and building data repositories by investigating storage formats and technologies for large-scale data [17].…”

Section: Related Workmentioning

confidence: 99%

Data Lake Conceptualized Web Platform for Food Research Data Collection

An,

Oh,

Kim

et al. 2024

JWE

View full text Add to dashboard Cite

Food research is uniquely intertwined with everyday life and necessitates the utilization of big data. Within this domain, the research data consist of various forms and formats, encompassing biological experiment results, chemical analysis data, nutritional information, microbiological data, sensor data, images, and videos. This diversity stems from the integration of data from various subdomains within the larger field. With recent advancements in deep learning technology, the importance of data has grown significantly, resulting in increased reliance on data-driven research. Although specialized platforms for sharing and utilizing data have been established at the national level, particularly in the bioscience field, food research lacks a dedicated infrastructure and specialized data-sharing platforms. In this study, we develop a platform that leverages Hadoop-based distributed file systems to create a data lake. This platform enables data storage and sharing through a web-based interface. The distributed file system supports scalability by adding data nodes, making it an effective solution for capacity expansion. In addition, the web-based platform ensures high accessibility, allowing users access from anywhere, at any time, using any device. Finally, we introduce the establishment of a 1.8 PB Hadoop-based physical storage system and present an approach for building a highly accessible web platform with substantial utility.

show abstract

“…Combined with the final model, it is applied to the field of education to analyze students' learning efficiency. Big data and the dynamic system studied in this paper represent the embodiment of human new thinking and the trend of updating technology in the information age (Belov Vladimir et al 2021) [9].…”

Section: Related Workmentioning

confidence: 99%

Dynamic Modeling of Influencing Factors and Change Trend of College Students' Mental Health Based on Big Data

2022

Scientific Programming

View full text Add to dashboard Cite

With the great changes of social development environment and the lack of psychological preparation of many students, many college students have many psychological problems in the process of adapting to the environment. If the problem cannot be solved in time, it will seriously affect their future adaptation and mental health. In order to solve the psychological problems of college students, the networked dynamic model constructed by using big data modeling technology can realize the system functions required by users and model the model accordingly. The main research direction of this paper is to study the influencing factors and change trend of college students' mental health under the background of big data. In the network-oriented scenario, the missing value of the data is supplemented, and the sequence prediction technology is added to the data. Finally, by adding corresponding data samples to the improved big data dynamic model, the results of the addition completion method and data sequence prediction technology are analyzed.

show abstract

Experimental Characteristics Study of Data Storage Formats for Data Marts Development within Data Lakes

Cited by 5 publications

References 22 publications

Modelling of Data Warehouse With Making the Trend to Make Decision in Company Xyz

Modelling of Data Warehouse With Making the Trend to Make Decision in Company Xyz

Data Lake Conceptualized Web Platform for Food Research Data Collection

Dynamic Modeling of Influencing Factors and Change Trend of College Students' Mental Health Based on Big Data

Contact Info

Product

Resources

About