Simple-talking database development: Let the end-user design a relational schema by using simple words

Protogeros, Nicolaos; Tzafilkou, Katerina

doi:10.1016/j.chb.2015.02.002

Cited by 11 publications

(4 citation statements)

References 25 publications

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“…But fortunately, as technology develops, studies and experts have come up with approaches that allow even people who are unfamiliar with database programming to create web applications and their databases easily. A few examples of the approaches said are model-driven [19,21] and goal-driven approaches [22,23].…”

Section: Operational Maintenancementioning

confidence: 99%

Designing and Using a MySQL Database for Human Resource Management

Madyatmadja¹,

Adora²

2019

Adv. sci. technol. eng. syst. j.

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In this paper, we would like to discuss the methods and ideologies used to create a database to be used for Human Resource purposes. Because we want this database to be accessible anywhere at any time, it is safe to conclude that an internet-based (web-based) database would work best, therefore we chose MySQL as the database management system. Before diving deep into the making of the database itself, it is important to understand certain basics of database design and the phases of the database life cycle itself. This paper will conclude on a few of the basic things to understand before designing a database for Human Resource Management on MySQL.

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Section: Operational Maintenancementioning

confidence: 99%

Designing and Using a MySQL Database for Human Resource Management

Madyatmadja¹,

Adora²

2019

Adv. sci. technol. eng. syst. j.

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“…Multiple algorithms for processing replications and executing queries for updating data in tables have been reviewed. Other approaches to detecting and analyzing errors during the conceptual data modeling are presented in [7] and [8]. The results show that these approaches can be used successfully in the design of databases.…”

Section: Literature Reviewmentioning

confidence: 99%

Design and Analysis of a Relational Database for Behavioral Experiments Data Processing

et al. 2018

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Abstract-This paper presents the results of a comparative analysis between different approaches to experimental data storage and processing. Several studies related to the problem and some methods for solving it have been discussed. Different types of databases, ways of using them and the areas of their application are analyzed. For the purposes of the study, a relational database for storing and analyzing specific data from behavioral experiments was designed. The methodology and conditions for conducting the experiments are described. Three different indicators are analyzed, respectively: memory required to store the data, time to load the data from an external file into computer memory and iteration time across all records through one cycle. The obtained results show that for storing a large number of records (in the order of tens of millions rows) either dynamic arrays (stored on external media in binary file format), or an approach based on a local or remote database management system can be used. Regarding the data loading time, the fastest approach was the one that uses dynamic arrays. It outperforms significantly the approaches based on a local or remote database. The obtained results show that the dynamic arrays and the local data sets approaches iterated much faster across all data records than the remote database approach.

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“…The second approach is that the data is imported into a pre-designed local or remote database, from which the summary information is then extracted for analysis via SQL queries [30]. Access to such a database can be done through a database management system-DBMS [1], [31]. Architectures of multi-user systems based on remote database servers with the ability to perform calculations and analysis of experimental data have been presented in other research [21], [30].…”

Section: Introductionmentioning

confidence: 99%

Data modelling and data processing generated by human eye movements

Kralev

Kraleva

Koprinkova–Hristova

2021

IJECE

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Data modeling and data processing are important activities in any scientific research. This research focuses on the modeling of data and processing of data generated by a saccadometer. The approach used is based on the relational data model, but the processing and storage of the data is done with client datasets. The experiments were performed with 26 randomly selected files from a total of 264 experimental sessions. The data from each experimental session was stored in three different formats, respectively text, binary and extensible markup language (XML) based. The results showed that the text format and the binary format were the most compact. Several actions related to data processing were analyzed. Based on the results obtained, it was found that the two fastest actions are respectively loading data from a binary file and storing data into a binary file. In contrast, the two slowest actions were storing the data in XML format and loading the data from a text file, respectively. Also, one of the time-consuming operations turned out to be the conversion of data from text format to binary format. Moreover, the time required to perform this action does not depend in proportion on the number of records processed.

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Simple-talking database development: Let the end-user design a relational schema by using simple words

Cited by 11 publications

References 25 publications

Designing and Using a MySQL Database for Human Resource Management

Designing and Using a MySQL Database for Human Resource Management

Design and Analysis of a Relational Database for Behavioral Experiments Data Processing

Data modelling and data processing generated by human eye movements

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