Resolving data duplication, inaccuracy and inconsistency issues using Master Data Management

Haneem, Faizura; Ali, Rosmah; Kama, Nazri; Basri, Sufyan

doi:10.1109/icriis.2017.8002453

Cited by 16 publications

(14 citation statements)

References 12 publications

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“…), product master data (product id#, product name, product unit), customer master data (customer id#, customer name, and address, etc.) [8,34]. The master data facilitate the fundamental data entities of the government to attain a data-driven administration [79].…”

Section: Master Reference Metadata and Transactional Datamentioning

confidence: 99%

Government Big Data Ecosystem: Definitions, Types of Data, Actors, and Roles and the Impact in Public Administrations

Shah

Peristeras

Magnisalis

2021

J. Data and Information Quality

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The public sector, private firms, business community, and civil society are generating data that are high in volume, veracity, and velocity and come from a diversity of sources. This type of data is today known as big data. Public administrations pursue big data as “new oil” and implement data-centric policies to collect, generate, process, share, exploit, and protect data for promoting good governance, transparency, innovative digital services, and citizens’ engagement in public policy. All of the above constitute the Government Big Data Ecosystem (GBDE). Despite the great interest in this ecosystem, there is a lack of clear definitions, the various important types of government data remain vague, the different actors and their roles are not well defined, while the impact in key public administration sectors is not yet deeply understood and assessed. Such research and literature gaps impose a crucial obstacle for a better understanding of the prospects and nascent issues in exploiting GBDE. With this study, we aim to start filling the above-mentioned gaps by organizing our findings from an extended Systematic Literature Review into a framework to organise and address the above-mentioned challenges. Our goal is to contribute in this fast-evolving area by bringing some clarity and establishing common understanding around key elements of the emerging GBDE.

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Section: Master Reference Metadata and Transactional Datamentioning

confidence: 99%

Government Big Data Ecosystem: Definitions, Types of Data, Actors, and Roles and the Impact in Public Administrations

Shah

Peristeras

Magnisalis

2021

J. Data and Information Quality

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“…Data Quality trait is a measure for qualitative or quantitative analysis in order to determine the quality of data [4].The major issue is that data is initially taken either from single source or multiple sources. The scattered data over different locations make the data unfit for use as it leads to quality issues such as duplicity of information inconsistency and incompleteness [6]. In "AGE" column, only integer value is allowed rather than character, string or time.…”

Section: A Data Quality Traitsmentioning

confidence: 99%

“…Table I describes the necessary traits for adequate data quality in creating master data. It is suggested that these traits and standards should be adopted by data quality professionals as these designed methods are useful for accessing and maintaining the level of data quality [6].…”

Section: A Data Quality Traitsmentioning

confidence: 99%

Data Profiling Model for Assessing the Quality Traits of Master Data Management

Singh¹,

Kaur²

2020

IJRTE

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Enterprise Resource Planning (ERP) and Business Intelligence (BI) system demand progressive rules for maintaining the valuable information about customers, products, suppliers and vendors as data captured through different sources may not be of high quality due to human errors, in many cases. The problem encounters when this information is accessible across multiple systems, within same organization. Providing adequacy to this scattered data is a top agenda for any organization as maintaining the data is complicated, as having high quality data. Master Data Management (MDM) provides a solution to these problems by maintaining “a single reference of truth” with authoritative source of master data (Customer, products, employees etc). Master Data Management (MDM) is a highlighted concern now a day as valid data is the demand for strategic, tactical and operational steering of every organization. The lane to MDM initiates with the quality of data which demands for discovery of master data, profiling and analysis. As inadequacy of data may leads to adverse effects such as wrong decision, loss of time, bad results and unnecessary risk. Thus there is a need to deal with master data and quality of this specific data in a successful and efficient manner. For ensuring this purpose, an approach is proposed in this paper. The research focuses on development of a Model for Data Profiling to assess the level of Quality Traits for Master Data Management. Results are shown by executing the defined steps on TALEND tool over collected dataset. Thus, level of quality traits processes directly correlates with an organization’s ability to make the proper decisions and better outcomes.

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“…To solve these problems, the work in [6] proposed to use MDM (Master Data Management) to resolve the issues of data duplication, inaccuracy and inconsistency. Baghi designed an architecture for master data application toward a decision model and it verified that the master data application architecture is better at the data quality aspect [7].…”

Section: Figure 1 the Traditional Data Sharing Model In Universitiesmentioning

confidence: 99%

Research on Centralized Data-Sharing Model Based on Master Data Management

et al. 2017

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This research aims to analyse the data-sharing model widely used in information centres of Chinese universities. A university centralized data-sharing model (UCDSM) based on master data management system was proposed to provide unified data standards, exchange services, data-quality control and comprehensive data-sharing services for universities in big data environment. Then the core implementation methods of this data-sharing model were analysed and implemented. Finally, the application results show that the UCDSM can support large-scale data sharing for digital campus and all the data transmission processes can be monitored and managed under a unified management platform. 1 Introduction With the rapid development of digital campus, many colleges and universities in China have built tremendous independent systems providing diverse services for different user groups in the campus [1][2]. University Centralized Database DBs in Business Area1 DBs in Business Area n.

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Resolving data duplication, inaccuracy and inconsistency issues using Master Data Management

Cited by 16 publications

References 12 publications

Government Big Data Ecosystem: Definitions, Types of Data, Actors, and Roles and the Impact in Public Administrations

Government Big Data Ecosystem: Definitions, Types of Data, Actors, and Roles and the Impact in Public Administrations

Data Profiling Model for Assessing the Quality Traits of Master Data Management

Research on Centralized Data-Sharing Model Based on Master Data Management

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