RGMDV: An approach to requirements gathering and the management of data virtualization projects

Mousa, Ayad Hameed; Shiratuddin, Norshuhada; Bakar, Muhamad Shahbani Abu

doi:10.1063/1.4937043

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…Business Intelligence (BI) is the mechanism to provide insights for most of the operations and performance of organizations, in addition to identifying strategic business opportunities. BI from a technical point is a set of techniques, tools and methodologies that work together to transform theinformation and data belongingto the organizations into meaningful and actionable information and making this information available to decision makers in an organization [1][2][3][4][5][6][7][8][9][10]. Usability testing is anextremely important element in software development.…”

Section: Introductionmentioning

confidence: 99%

An Evaluation Instrument (Q-U) for Measuring the usability of Business Intelligence Application

Mousa¹,

Raheem²,

Mohammed³

2018

IJET

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The main purpose of Business Intelligence (BI) applications is to focus on supporting organizations' strategic, operational a nd tactical decisions by providing comprehensive, accurate and vivid data to the decision makers. Usability testing is an important part of software development. It focuses on how well users can understand and utilize a product/software in fulfilling their intended goals. In the software development, most software tends to be complex. Hence, the way to ensure that such software will satisfy users will be done by measuring the usability of such software. Due to using many data integration techniques in developing BI application, thus, the different software have different instruments to measure the usability of BI software. In this paper, the new instrument (Q-U) for measuring BI software was developed. A systematic approach was adopted which suggested by many researchers in developing the intended Q-U instrument.The literature has been reviewed in a systematic manner to elicitation Q-U instrument attributes. Multi-methods were used in validating Q-U instrument such as face validity, a pilot study for testing the goodness of Q-U consistency, and factor analysis. Multi-methods were used in validating Q-U instrument such as face validity, a pilot study for testing the goodness of Q-U consistency, and factor analysis as well as Bartlett's test for measuring the reliability of Q_U. The finding obtained indicates the workability of Q_U in measuring the usability OF BI applications. Ultimately, Q_U was used in measuring BI application in two different sectors.

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Section: Introductionmentioning

confidence: 99%

An Evaluation Instrument (Q-U) for Measuring the usability of Business Intelligence Application

Mousa¹,

Raheem²,

Mohammed³

2018

IJET

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“…Technically, data mining technology is about gathering data from heterogeneous and homogeneous databases, cleaning and cleansing the intended data of any missing values, and finally applying some statistical queries to discover meaningful information from the intended data. There is a limitation in using data mining in the healthcare sector, these limitations emerged because of no enough methodologies which used to elicit meaningful information from medical data [3][4][5][6]. In the healthcare sector, medical data mining plays an important role by providing plenty of possibilities.…”

Section: Introductionmentioning

confidence: 99%

Limbless Medical Data Analyzing using CRISP Model a Case Study of UK Limbless Patients

Alden¹,

Mousa²

2018

IJET

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Data mining, usually known as knowledge elicitation in the field of computer science databases, is the procedure to find out an important relationship, useful patterns in a huge amount of raw data. Besides, many sectors have adapted and used data mining in their applications such as healthcare and industry sector. In the healthcare sector, data mining can help in determining the probability of particular health cases in medical issues which the related variables pre-known as well as predicting future events. The availability of medical data for data mining usually exist in a raw data format, therefore, it needs for making ready and exploration to be willing to use. In the context of this paper, an analyzing of medical data was introduced to support prosthetics service centers to analyze find out the significant information from limbless medical cases, besides, in providing a comprehensive understanding of amputation and its types as well as the level of amputation. To ensure extract meaningful information from the intended data sets as well as to follow a systematic approach, the CRISP-DM model was adopted. The findings show the important and meaningful of the analyzing data using data mining modes.

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Data and Computation Movement in Fog Environments: The DITAS Approach

et al. 2018

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RGMDV: An approach to requirements gathering and the management of data virtualization projects

Cited by 3 publications

References 12 publications

An Evaluation Instrument (Q-U) for Measuring the usability of Business Intelligence Application

An Evaluation Instrument (Q-U) for Measuring the usability of Business Intelligence Application

Limbless Medical Data Analyzing using CRISP Model a Case Study of UK Limbless Patients

Data and Computation Movement in Fog Environments: The DITAS Approach

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