Abstract
Master data management (MDM) can provide an integrated and unified view of key business entities to offer better support in business processes. Due to the very nature of master data-based applications, it is possible to use data with the highest possible level of quality. MDM can help ensure that some common concerns, like duplicates or inconsistencies, are prevented by sharing a ‘single version of the truth’ throughout the organisation, and, in some cases, allowing collaborative updates to the master data repository. Therefore, assuring the reliability of master data-based applications, would improve the organisation efficiency. This type of application should implement a set of functional requirements covering the basic operation of MDM principles. We propose a solution based on the evaluation and certification of ‘functional suitability’ of MDM applications. As part of our proposal, we inferred a set of functional requirements from parts 100 to 140 of ISO 8000. This set will be used as a reference in the required matching to compute values for each one of the metrics, properties, subcharacteristics and ultimately, functional suitability following a bottom-up procedure. Finally, the paper also describes the application of the evaluation procedure of an existing master data-based application.
Similar content being viewed by others
References
Allen, M., & Cervo, D. (2015). Multi-domain master data management: Advanced MDM and data governance in practice. Morgan Kaufmann.
Blanco, A., Reales, P. & Rodriguez, M. (2012). Metrics to evaluate functional quality: A systematic review., Proceedings of Conferencia Ibérica de Sistemas y Tecnologías de Información (CISTI 2012), Madrid, Spain.
Choi, M.-Y., Moon, C.-J., Park, K.-S. & Baik, D.-K. (2010) An enterprise master data model based on the data taxonomy based on their origin, Proceeding of International Conference on Enterprise Information Systems and Web Technologies (EISWT 2010), pp. 34–41.
Cleven, A. & Wortmann, F. (2010). Uncovering four strategies to approach master data management, Proceeding of the 43rd Hawaii International Conference on System Sciences 2010, pp. 1–10.
Dreibelbis, A., Hechler, E., Milman, I., Oberhofer, M., van Run, P., & Wolfson, D. (2008). Enterprise Master Data Management (Paperback): An SOA Approach to Managing Core Information. Pearson Education.
Fleckenstein, M., & Fellows, L. (2018). Modern Data Strategy. Springer International Publishing.
Forrester (2019) The Forrester Wave: Master Data Management, Q1 2019. https://cutt.ly/1ricvfb Last accessed in December 2019.
Gartner (2018) Magic Quadrant for Master Data Management Solutions. https://cutt.ly/Fricny3 Last accessed in December 2019.
ISO (2009), ISO 8000-110:2009 Data quality -- Part 110: Master data: Exchange of characteristic data: Syntax, semantic encoding, and conformance to data specification. International Standardization for Organization (ISO).
ISO (2011a), ISO/IEC 25010:2011 Systems and software engineering -- Systems and software Quality Requirements and Evaluation (SQuaRE) -- System and software quality models. ISO/IEC.
ISO (2011b), ISO/IEC 25040:2011 Systems and software engineering -- Systems and software Quality Requirements and Evaluation (SQuaRE) -- Evaluation process. ISO/IEC.
ISO (2011c), ISO 8000-150:2011 Data quality -- Part 150: Master data: Quality management framework. International Standardization for Organization.
ISO (2016a), ISO 8000-100:2016 Data quality -- Part 100: Master data: Exchange of characteristic data: Overview. International Standardization for Organization.
ISO (2016b), ISO 8000-120:2016 Data quality -- Part 120: Master data: Exchange of characteristic data: Provenance. International Standardization for Organization.
ISO (2016c), ISO 8000-130:2016 Data quality -- Part 130: Master data: Exchange of characteristic data: Accuracy. International Standardization for Organization.
ISO (2016d), ISO 8000-140:2016 Data quality -- Part 140: Master data: Exchange of characteristic data: Completeness. International Standardization for Organization.
ISO (2018a), ISO 8000-115:2018 Data quality -- Part 115: Master data: Exchange of quality identifiers: Syntactic, semantic and resolution requirements. International Standardization for Organization.
ISO (2019), ISO 8000–116 Data quality -- Part 116: Application of ISO 8000-115 to the formatting of Authoritative Legal Entity Identifiers (ALEI) for individuals and organizations. International Standardization for Organization.
Loshin, D. (2010). Master Data Management. Morgan Kaufmann.
Mahanti, R. (2019). Data quality: Dimensions, Measurement, Strategy, Management, and Governance. ASQ Quality Press.
Otto, B., Ebner, V. & Hüner, K. M. (2010) Measuring master data quality: Findings from a case study. Proceedings of 16th Americas Conference on Information Systems (AMCIS 2010), 5, 3761–3769.
Otto, B., Hüner, K. M., & Österle, H. (2012). Toward a functional reference model for master data quality management. Information Systems and e-Business Management, 10(3), 395–425.
Rivas, B., Merino, J., Caballero, I., Serrano, M., & Piattini, M. (2017). Towards a service architecture for master data exchange based on ISO 8000 with support to process large datasets. Computer Standards & Interfaces, 54(2), 94–104.
Rodríguez, M., Piattini, M., & Fernandez, C. M. (2015). A hard look at software quality: Pilot program uses ISO/IEC 25000 family to evaluate, improve and certify software products. Quality Progress, 48(9), 30–36.
Rodríguez, M., Oviedo, J. R., & Piattini, M. (2016). Evaluation of software product functional suitability: A case study. Software Quality Professional Magazine, 18(3), 18–29.
Smith, H. A., & McKeen, J. D. (2008). Developments in practice XXX: master data management: salvation or snake oil?. Communications of the Association for Information Systems, 23(1), 63–72.
Spruit, M., & Pietzka, K. (2015). MD3M: The master data management maturity model. Computers in Human Behavior, 51, 1068-1076.
Talburt, J. R. (2011). Entity resolution and information quality. Elsevier.
Zúñiga, D. V., Cruz, R. K., Ibañez, C. R., Dominguez, F. & Moguerza, J. M. (2018) Master data management maturity model for the microfinance sector in Peru. ACM International Conference Proceeding Series, 49–53.
Funding
This research is partially funded by Industrial PhD DIN2018-009705, funded by the Spanish Ministry of Science, Innovation and Universities, GEMA: Generation and Evaluation of Models for dAta Quality (Ref.: SBPLY/17/180501/000293), DQIoT project (INNO-20171086 EUREKA Project No. E!11737), funded by CDTI, ECD project (PTQ-16-08504), funded by the ‘Torres Quevedo’ Program of the Spanish Ministry of Economy, Industry and Competitiveness, TESTIMO project (Consejería de Educación, Cultura y Deportes de la Junta de Comunidades de Castilla-La Mancha, and Fondo Europeo de Desarrollo Regional FEDER, SBPLY/17/180501/000503), and ECLIPSE project (RTI2018-094283-B-C31) funded by Ministry of Science, Innovation and Universities and FEDER funds.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix
Appendix
1.1 A certification environment for software quality based on ISO 25010 and ISO 25040
The environment for evaluation and certification of the functional suitability in software product quality against ISO 25010 is presented by Rodriguez et al. in (2015, 2016). This environment is used to evaluate and certify that a software product meets the functional requirements, and therefore, fulfils the purpose for which it was created. According to https://www.iso25000.com/index.php/en/certified-products, the environment has been used to certify more than 20 software products in different business areas: health, human resources, education, business intelligence, or risk management. However, this environment has not yet been used to certify MDM-based applications because of the specifics of this type of system, even an increasing demand of this service (Forrester 2019; Gartner 2018). This environment consists of a software quality model (which includes ‘functional suitability’ as introduced in ISO 25010 (ISO 2011a)), and an evaluation process based on ISO 25040 (ISO 2011b).
1.2 Functional suitability quality model
The software quality model contains the set of characteristics and subcharacteristics of the quality against which to evaluate a software product. As aforementioned, one of these software quality characteristics is ‘functional suitability’, which represents the ability of the software product to provide functions that meet the needs (stated and implied), when the product is used in specified conditions. This characteristic is split into the three following subcharacteristics:
-
‘Functional completeness’ is the degree to which the set of functions covers all the specified tasks and user objectives.
-
‘Functional correctness’ is the degree to which a product or system provides the correct results with the needed degree of precision.
-
‘Functional appropriateness’ is the degree to which the functions facilitate the accomplishment of specified tasks and objectives.
In addition, each one of the characteristics is split into one or more properties (see Fig. 6) that are used to evaluate the characteristic, and each property uses several metrics in order to calculate the value of the property. These metrics were extracted from the systematic review purposed by Blanco et al. in (Blanco et al. 2012).
1.3 Functional suitability evaluation process
The evaluation process for software products certification needs the evaluation of the software quality characteristics. For the sake of the replicability and accuracy of the results, the evaluation process specified in ISO 25040 (ISO 2011b) is encouraged. The evaluation includes the five activities represented in Fig. 7.
The main goal of the first activity is to establish the requirements and scope for the evaluation. During this activity, there are several meetings with stakeholders to present the evaluation process, the evaluation needs, and to determine the main characteristics and documentation about the MDM-based application aim of the evaluation. Additionally, in this first activity, the set of functional requirements to be met by an MDM-based application compliance to ISO 8000 parts 100 to 140 is specified, and the functional requirements of the MDM-based application with this set of reference is mapped. In the second activity, the main goal is to specify the evaluation. The third activity is aimed at defining the goal and planning for the evaluation. The plan should consider available resources for the evaluation. In the fourth activity, the main goal is to execute the evaluation activities according to the evaluation plan. Finally, the fifth and last activities consist of issuing the report with the results of the evaluation. This result of the evaluation should be informed to the applicant of the evaluation and those interested in this final activity.
Given the importance of activity 4, it is worth to further describing its goal. The evaluation process is performed by following a bottom-up approach, which begins by calculating the metrics identified at the bottom of Fig. 6 (number of requirements, number of requirements implemented, number of requirements tested, and requirements for user type). Some of these values can be calculated based on the execution of customised testing cases. The possible values of all these metrics are normalised and they range [0,100]. The values of these metrics are used to compute the properties (e.g. functional implementation completeness) defined in the immediately higher level. The possible values of these properties are also normalised and range [0, 100]. Analogously, the value of the properties is used to calculate the value of the subcharacteristics (e.g. functional completeness). The value of the subcharacteristics is also normalised and range [0,100]. Finally, after calculating the subcharacteristic values, it is necessary to compute these results to obtain a value for the functional suitability. The procedure to compute the metrics to determine the quality level of each quality characteristic and the quality level for the evaluation of the functional adequacy of a software product are available in (Rodríguez et al. 2016). The quality level of functional suitability is represented on a level scale expressed in a range from 1 to 5, where 1 is the lowest level and 5 is the highest.
Rights and permissions
About this article
Cite this article
Gualo, F., Caballero, I. & Rodriguez, M. Towards a software quality certification of master data-based applications. Software Qual J 28, 1019–1042 (2020). https://doi.org/10.1007/s11219-019-09495-w
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11219-019-09495-w