Log in

Relevant bibliographies by topics / Data maturity / Journal articles

To see the other types of publications on this topic, follow the link: Data maturity.

Journal articles on the topic 'Data maturity'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Data maturity.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Knoflach, Lukas, Lin Shao, and Torsten Ullrich. "A Comprehensive Data Maturity Model for Data Pre-Analysis." Data 10, no. 4 (2025): 55. https://doi.org/10.3390/data10040055.

Full text

Abstract:

Data analysis is widely used in research and industry where there is a need to extract information from data. A significant amount of time within a data analysis project is required to prepare the data for subsequent analysis. This paper presents a comprehensive weighted maturity model to estimate the readiness of data for subsequent data analysis, with the goal of avoiding delays due to data quality problems. The maturity model uses a questionnaire with nine criteria to determine the maturity level of data preparation. The maturity model is integrated into a web application that provides an a

APA, Harvard, Vancouver, ISO, and other styles

2

Hochkamp, Florian, Anne Antonia Scheidler, and Markus Rabe. "Review of Maturity Models for Data Mining and Proposal of a Data Preparation Maturity Model Prototype for Data Mining." Computers 14, no. 4 (2025): 146. https://doi.org/10.3390/computers14040146.

Full text

Abstract:

Companies face uncertainties evaluating their own capabilities when implementing data analytics or data mining. Data mining is a valuable process used to analyze data and support decisions based on the knowledge generated, creating a pipeline from the phases of data collection to data preparation and data mining. In order to assess the target state of a company in terms of its data mining capabilities, maturity models are viable tools. However, no maturity models exist that focus on the data mining process and its particular phases. This article discusses existing maturity models in the broade

APA, Harvard, Vancouver, ISO, and other styles

3

Wagner, Michael, and Christin Henzen. "Quality Assurance for Spatial Research Data." ISPRS International Journal of Geo-Information 11, no. 6 (2022): 334. http://dx.doi.org/10.3390/ijgi11060334.

Full text

Abstract:

In Earth System Sciences (ESS), spatial data are increasingly used for impact research and decision-making. To support the stakeholders’ decision, the quality of the spatial data and its assurance play a major role. We present concepts and a workflow to assure the quality of ESS data. Our concepts and workflow are designed along the research data life cycle and include criteria for openness, FAIRness of data (findable, accessible, interoperable, reusable), data maturity, and data quality. Existing data maturity concepts describe (community-specific) maturity matrices, e.g., for meteorological

APA, Harvard, Vancouver, ISO, and other styles

4

Cech, Thomas G., Trent J. Spaulding, and Joseph A. Cazier. "Data competence maturity: developing data-driven decision making." Journal of Research in Innovative Teaching & Learning 11, no. 2 (2018): 139–58. http://dx.doi.org/10.1108/jrit-03-2018-0007.

Full text

Abstract:

Purpose The purpose of this paper is to lay out the data competence maturity model (DCMM) and discuss how the application of the model can serve as a foundation for a measured and deliberate use of data in secondary education. Design/methodology/approach Although the model is new, its implications, and its application are derived from key findings and best practices from the software development, data analytics and secondary education performance literature. These principles can guide educators to better manage student and operational outcomes. This work builds and applies the DCMM model to se

APA, Harvard, Vancouver, ISO, and other styles

5

Surendranadha Reddy Byrapu Reddy. "Unified Data Analytics Platform For Financial Sector Using Big Data." Tuijin Jishu/Journal of Propulsion Technology 44, no. 4 (2023): 3878–85. http://dx.doi.org/10.52783/tjjpt.v44.i4.1560.

Full text

Abstract:

Organizations in today's data-driven digital economy are seeking ways to leverage the immense value of massive amounts of information so as to make more informed decisions. They are able to not only uncover new prospects, but also learn more and improve their performance thanks to big data analytics. Although many businesses have poured resources into big data analytics projects, most have failed to reap the benefits. While there has been a lot of research into the topic of big data analytics, relatively little is known about the strategies that organizations use to merge the various aspects o

APA, Harvard, Vancouver, ISO, and other styles

6

Berndtsson, Mikael, and Stefan Ekman. "Assessing Maturity in Data-Driven Culture." International Journal of Business Intelligence Research 14, no. 1 (2023): 1–17. http://dx.doi.org/10.4018/ijbir.332813.

Full text

Abstract:

Research on assessing a group's maturity in data-driven culture is rare and fragmented. This article investigates how maturity in data-driven culture can be assessed from a historical perspective. A case study was done on how the Education Council evolved in analytics maturity and as a group during 2014-2023. The assessment showed that the Education Council experienced both successful progression of group development and usage of analytics, as well as regression in group development and analytics usage. The practical implications of the findings are that group leaders need to be aware of the i

APA, Harvard, Vancouver, ISO, and other styles

7

Wilantika, Nori, and Wahyu Catur Wibowo. "Data Quality Management in Educational Data." Jurnal Sistem Informasi 15, no. 2 (2019): 52–67. http://dx.doi.org/10.21609/jsi.v15i2.848.

Full text

Abstract:

Every varsity in Indonesia is responsible for ensuring the completeness, the validity, the accuracy, and the currency of its educational data. The educational data is used for implementing higher-education quality assurance system and formulating policies related to universities and majors in Indonesia. Data quality assessment result indicates that educational data in Statistics Polytechnic did not meet completeness, validity, accuracy, and currency criteria. Data quality management maturity has been measured using Loshin’s Data Quality Maturity Model which result is in level 1 to level 2 of m

APA, Harvard, Vancouver, ISO, and other styles

8

Schmuck, Matthias. "Master data management as part of data governance: A maturity model to improve efficiency and trust in master data and thus business performance." Business Performance Review 2, no. 2 (2024): 20–34. http://dx.doi.org/10.22495/bprv2i2p2.

Full text

Abstract:

An optimized master data management correlates with improved data quality, enhanced process integration and increased business agility, leading to overall better business performance. This study proposes a maturity model for structured master data management improvement that has emerged from analysing previous maturity model research, data governance, master data management and the practical experience of the researcher. The model comprises six maturity levels for eight design levels with 23 assessment factors, which are framed by six organizational factors. It extends previous maturity models

APA, Harvard, Vancouver, ISO, and other styles

9

Ryu, Kyung Seok, Joo Seok Park, and Jae Hong Park. "A Data Quality Management Maturity Model." ETRI Journal 28, no. 2 (2006): 191–204. http://dx.doi.org/10.4218/etrij.06.0105.0026.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Stalla-Bourdillon, Sophie. "A Maturity Spectrum for Data Institutions." IEEE Security & Privacy 19, no. 5 (2021): 90–94. http://dx.doi.org/10.1109/msec.2021.3094985.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Solar, Mauricio, Fernando Daniels, Roberto López, and Luis Meijueiro. "A Model to Guide the Open Government Data Implementation in Public Agencies." JUCS - Journal of Universal Computer Science 20, no. (11) (2014): 1564–82. https://doi.org/10.3217/jucs-020-11-1564.

Full text

Abstract:

This paper presents a model to diagnose maturity and capabilities of Public Agencies (PAs) in pursuing the open data principles and practices. The open data maturity model, called OD-MM, was piloted in ten PAs from three Latin American countries, validating in this way the web tool that operationalizes the model. This web tool is a valuable diagnostic tool for PA's, since it shows all weaknesses and provides the instrument (a roadmap) to progress in the implementation of open data. We also propose a guide to implement open data in PAs. This guide is the result of the OD-MM application in Latin

APA, Harvard, Vancouver, ISO, and other styles

12

Zhou, Qiu Zhong, and Hao Yu Zha. "Application of Data Maturity in Product Development Process Control." Applied Mechanics and Materials 58-60 (June 2011): 657–61. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.657.

Full text

Abstract:

In the concurrent and collaborative product development process, the realization of quantitative analysis and overall control of the development process management is the key and the difficulties in the current study. Through describes the concept and role of data maturity, a new methods to quantitative analysis and overall control of collaborative product development process based on the idea of data maturity was proposed in this paper. Base on the explanation of the theory of data maturity to control the process, the differences and relationship between data maturity and milestone was analyz

APA, Harvard, Vancouver, ISO, and other styles

13

Spruit, Marco, and Catalina Sacu. "DWCMM: The Data Warehouse Capability Maturity Model." JUCS - Journal of Universal Computer Science 21, no. (11) (2015): 1508–34. https://doi.org/10.3217/jucs-021-11-1508.

Full text

Abstract:

Data Warehouses and Business Intelligence have become popular fields of research in recent years. Unfortunately, in daily practice many Data Warehouse and Business Intelligence solutions still fail to help organizations make better decisions and increase their profitability, due to intransparent complexities and project interdependencies. In addition, emerging application domains such as Mobile Learning & Analytics heavily depend on a well-structured data foundation with a longitudinally prepared architecture. Therefore, this research presents the Data Warehouse Capability Maturity Model (

APA, Harvard, Vancouver, ISO, and other styles

14

-, Siti Resmi. "Analisis Faktor Penentu Harga Obligasi Korporasi di Bursa Efek Indonesia." Jurnal Riset Akuntansi dan Auditing 9, no. 2 (2022): 1–13. http://dx.doi.org/10.55963/jraa.v9i2.461.

Full text

Abstract:

Penelitian ini bertujuan untuk menguji pengaruh likuiditas, maturitas, dan yield to maturity terhadap harga obligasi korporasi. Subjek dalam penelitian ini adalah korporasi yang terdaftar di Bursa Efek Indonesia periode 2017 – 2019. Sampel diperoleh menggunakan teknik purposive sampling. Data pada penelitian ini adalah data sekunder berupa data statistik tahunan. Terdapat 23 seri obligasi korporasi dan 69 data observasi yang di uji pada penelitian ini. Pengujian dilakukan menggunakan regresi data panel. Hasil penelitian menunjukkan bahwa likuiditas berpengaruh tidak signifikan terhadap harga o

APA, Harvard, Vancouver, ISO, and other styles

15

Comuzzi, Marco, and Anit Patel. "How organisations leverage Big Data: a maturity model." Industrial Management & Data Systems 116, no. 8 (2016): 1468–92. http://dx.doi.org/10.1108/imds-12-2015-0495.

Full text

Abstract:

Purpose While it is commonly recognised that Big Data have an immense potential to generate value for business organisations, appropriating value from Big Data and, in particular, Big Data-enabled analytics is still an open issue for many organisations. The purpose of this paper is to develop a maturity model to support organisations in the realisation of the value created by Big Data. Design/methodology/approach The maturity model is developed following a qualitative approach based on literature analysis and semi-structured interviews with domain experts. The completeness and usefulness of th

APA, Harvard, Vancouver, ISO, and other styles

16

Knoke, Friederike, and Iheanyi Nwankwo. "Managing Data Protection Compliance through Maturity Models: A Primer." European Data Protection Law Review 8 ( 2022), no. 4 (2022): 536–43. https://doi.org/10.21552/edpl/2022/4/14.

Full text

Abstract:

The quest to comply with the GDPR since its adoption in 2016 has given rise to several models suggesting how to comply with the various requirements of the regulation. These models focus on different aspects of data protection; for example, the Standard Data Protection Model (SDM) 1 focuses on implementing technical and organisational measures, while the Privacy Risk Analysis Methodology PRIAM2 is a privacy risk assessment model. A slightly different way of approaching compliance is using amaturitymodel. Amaturitymodelis amodel to describe and evaluate how an entity makes progress in achieving

APA, Harvard, Vancouver, ISO, and other styles

17

Al-Sai, Zaher Ali, Mohd Heikal Husin, Sharifah Mashita Syed-Mohamad, et al. "Big Data Maturity Assessment Models: A Systematic Literature Review." Big Data and Cognitive Computing 7, no. 1 (2022): 2. http://dx.doi.org/10.3390/bdcc7010002.

Full text

Abstract:

Big Data and analytics have become essential factors in managing the COVID-19 pandemic. As no company can escape the effects of the pandemic, mature Big Data and analytics practices are essential for successful decision-making insights and keeping pace with a changing and unpredictable marketplace. The ability to be successful in Big Data projects is related to the organization’s maturity level. The maturity model is a tool that could be applied to assess the maturity level across specific key dimensions, where the maturity levels indicate an organization’s current capabilities and the desirab

APA, Harvard, Vancouver, ISO, and other styles

18

Pörtner, Lara, Andreas Riel, Benedikt Schmidt, Marcel Leclaire, and Robert Möske. "Data Management Maturity Model—Process Dimensions and Capabilities to Leverage Data-Driven Organizations Towards Industry 5.0." Applied System Innovation 8, no. 2 (2025): 41. https://doi.org/10.3390/asi8020041.

Full text

Abstract:

Data-driven organizations aim to control business decisions based on data. However, despite significant investments in digitalization, studies show that many organizations continue to face challenges in fully realizing the benefits of data. Existing maturity models for digital transformation, data management, and data-driven organizations lack a comprehensive, industry-agnostic, and practically validated approach to addressing industry challenges. This work introduces a refined data management maturity model developed using De Bruin’s maturity model assessment methodology. The model aims to in

APA, Harvard, Vancouver, ISO, and other styles

19

Sigi, Awit Lela. "Designing Data Governance With DAMA DMBOK Framework." Jurnal Teknobisnis 8, no. 2 (2024): 79–89. http://dx.doi.org/10.12962/j24609463.v8i2.1408.

Full text

Abstract:

The vitality of data in aiding companies to fulfill their organizational objectives is paramount, as it can shape decisions across a variety of business operations. Often, corporations overlook the significance of data management, which in fact demands serious consideration. Two key issues that are frequently neglected include the hazy assignment of data responsibilities and the lack of robust data governance. The absence of transparency in data sources can interfere with data analysis or processing, while insufficient data integration and synchronization can prolong report creation time up to

APA, Harvard, Vancouver, ISO, and other styles

20

Laposa, Tamás, and Gáspár Frivaldszky. "Data Protection Maturity: an analysis of methodological tools and frameworks." Central and Eastern European eDem and eGov Days 338 (July 15, 2020): 135–47. http://dx.doi.org/10.24989/ocg.338.11.

Full text

Abstract:

This paper discusses the maturity of data protection and privacy measures in order to develop a better understanding of the importance and impacts of this domain. The practical relevance of this topic is that the General Data Protection Regulation provides that data controllers in EU Member States shall comply with uniform data protection rules. Even though European legislation sets detailed requirements for data controllers, the implementation of appropriate technical and organisational measures can be realised at different levels of maturity. Based on the analysis of the pertinent lite

APA, Harvard, Vancouver, ISO, and other styles

21

Ershov, Peter Sergeevich, Alexander Vladimirovich Katin, Yuri Evgenyevich Hohlov, and Sergei Borisovich Shaposhnik. "Big Data for Digital Economy Maturity Model." Information Society, no. 4-5 (2021): 259–77. http://dx.doi.org/10.52605/16059921_2021_04_259.

Full text

APA, Harvard, Vancouver, ISO, and other styles

22

Zangana, Hewa Majeed. "ITD Data Quality Maturity (A Case Study)." International Journal of Engineering and Computer Science 8, no. 10 (2019): 24851–54. http://dx.doi.org/10.18535/ijecs/v8i10.4368.

Full text

Abstract:

Nowadays, more and more organizations are realizing of importance of their data, because it can be considered as an important asset in present nearly all business organizational processes. Information Technology Division (ITD) is a department in the International Islamic University Malaysia (IIUM) that consolidates efforts in providing IT services to the university. The university data management started with decentralized units, where each center or division has its own hardware and database system. Later it improved to become became centralized, and ITD is now trying to one policy acro

APA, Harvard, Vancouver, ISO, and other styles

23

Sen, A., K. Ramamurthy, and A. P. Sinha. "A Model of Data Warehousing Process Maturity." IEEE Transactions on Software Engineering 38, no. 2 (2012): 336–53. http://dx.doi.org/10.1109/tse.2011.2.

Full text

APA, Harvard, Vancouver, ISO, and other styles

24

BONCEA, Radu, Ionut PETRE, Dragos-Marian SMADA, and Alin ZAMFIROIU. "A Maturity Analysis of Big Data Technologies." Informatica Economica 21, no. 1/2017 (2017): 60–71. http://dx.doi.org/10.12948/issn14531305/21.1.2017.05.

Full text

APA, Harvard, Vancouver, ISO, and other styles

25

Spruit, Marco, and Katharina Pietzka. "MD3M: The master data management maturity model." Computers in Human Behavior 51 (October 2015): 1068–76. http://dx.doi.org/10.1016/j.chb.2014.09.030.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Hugo, W. "A Maturity Model for Digital Data Centers." Data Science Journal 12 (2013): WDS189—WDS192. http://dx.doi.org/10.2481/dsj.wds-032.

Full text

APA, Harvard, Vancouver, ISO, and other styles

27

Willetts, Matthew, and Anthony S. Atkins. "Big Data Analytics Maturity Model for SMEs." International Journal of Information Technology and Computer Science 16, no. 2 (2024): 1–15. http://dx.doi.org/10.5815/ijitcs.2024.02.01.

Full text

Abstract:

Small and medium-sized enterprises (SMEs) are the backbone of the global economy, constituting 90% of all businesses. Despite being widely adopted by large businesses who have reported numerous benefits including increased profitability and increased efficiency and a survey in 2017 of 50 Fortune 1000 and leading firms’ executives indicated that 48.4% of respondents confirmed they are achieving measurable results from their Big Data investments, with 80.7% confirming that they have generated business. Big Data Analytics is adopted by only 10% of SMEs. The paper outlines a review of Big Data Mat

APA, Harvard, Vancouver, ISO, and other styles

28

Tonnang, Henri E. Z., Tesfaye Balemi, Kenneth F. Masuki, et al. "Rapid Acquisition, Management, and Analysis of Spatial Maize (Zea mays L.) Phenological Data—Towards ‘Big Data’ for Agronomy Transformation in Africa." Agronomy 10, no. 9 (2020): 1363. http://dx.doi.org/10.3390/agronomy10091363.

Full text

Abstract:

Mobile smartphones, open-source set tools, and mobile applications have provided vast opportunities for timely, accurate, and seamless data collection, aggregation, storage, and analysis of agricultural data in sub-Saharan Africa (SSA). In this paper, we advanced and demonstrated the practical use and application of a mobile smartphone-based tool, i.e., the Open Data Kit (ODK), to assemble and keep track of real-time maize (Zea mays L.) phenological data in three SSA countries. Farmers, extension agents, researchers, and other stakeholders were enlisted to participate in an initiative to demon

APA, Harvard, Vancouver, ISO, and other styles

29

Zhang, Zhaotong, Bei Bian, and Yiping Jiang. "A Joint Decision-Making Approach for Tomato Picking and Distribution Considering Postharvest Maturity." Agronomy 10, no. 9 (2020): 1330. http://dx.doi.org/10.3390/agronomy10091330.

Full text

Abstract:

Fruit maturity is an essential factor for fresh retailers to make economical distribution scheduling and scientific market strategies. In the context of farm-to-door mode, the fresh retailers could incorporate the postharvest maturity time, picking time and distribution time to deliver high-quality fruits to consumers. This study selects climacteric tomato fruits and formulates a postharvest maturity model by capturing the firmness and soluble solid content (SSC) data during maturing. A joint picking and distribution model is proposed to ensure tomatoes could arrive at consumers within expecte

APA, Harvard, Vancouver, ISO, and other styles

30

Saputra, Ari Kurniawan, Riza Muhida, Yuthsi Aprilinda, and Fenty Ariani. "Maturity Level Assesment Tata Kelola Data Bantuan Sosial Menggunakan Domain Data Governance DAMA-DMBOK." Explore: Jurnal Sistem Informasi dan Telematika 14, no. 2 (2023): 177. http://dx.doi.org/10.36448/jsit.v14i2.3355.

Full text

APA, Harvard, Vancouver, ISO, and other styles

31

Gökalp, Mert Onuralp, Ebru Gökalp, Kerem Kayabay, Altan Koçyiğit, and P. Erhan Eren. "Data-driven manufacturing: An assessment model for data science maturity." Journal of Manufacturing Systems 60 (July 2021): 527–46. http://dx.doi.org/10.1016/j.jmsy.2021.07.011.

Full text

APA, Harvard, Vancouver, ISO, and other styles

32

Williams, Nigel, Nicole P. Ferdinand, and Robin Croft. "Project management maturity in the age of big data." International Journal of Managing Projects in Business 7, no. 2 (2014): 311–17. http://dx.doi.org/10.1108/ijmpb-01-2014-0001.

Full text

Abstract:

Purpose – While the area of project management maturity (PMM) is attracting an increased amount of research attention, the approaches to measuring maturity fit within existing social science conventions. This paper aims to examine the potential contribution of new data collection and analytical approaches to develop new insights in PMM. Design/methodology/approach – This paper takes the form of a literature review. Findings – The current trends of rapidly growing digital data collection and storage may have the potential to develop approaches to PMM assessment that overcome the limitations of

APA, Harvard, Vancouver, ISO, and other styles

33

SCHMUCK, MATTHIAS. "OPTIMIZATION OF MASTER DATA MANAGEMENT: A MATURITY MODEL." European Financial Resilience and Regulation, no. 8 (2025): 341–50. https://doi.org/10.47743/eufire-2024-1-26.

Full text

Abstract:

Master data management forms the foundation for the success of modern organizations by ensuring the quality, consistency and availability of data. Determining the maturity level of this management system is crucial to identify weaknesses and potential for improvement. This study presents a model for assessing the maturity of master data management because of analysing previous research findings on maturity models in general, master data management maturity models in particular, data governance and practical experiences. The proposed model provides a comprehensive assessment framework according

APA, Harvard, Vancouver, ISO, and other styles

34

Roze, Stéphane, Nicolas Bertrand, Lauriane Eberst, and Isabelle Borget. "Projecting overall survival data for health-economic models in oncology: Do maturity levels impact uncertainty?" Journal of Clinical Oncology 37, no. 15_suppl (2019): e18350-e18350. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.e18350.

Full text

Abstract:

e18350 Background: A lifetime horizon is recommended for health-economic evaluation of anticancer drugs. If overall survival (OS) data is immature, extrapolation of the Kaplan-Meier (KM) curve using distributions is done to obtain long-term data. Depending on OS maturity, the distribution chosen may impact estimation of life expectancy (LE) and of life years gained (LYG) between treatments. This study aimed to estimate the error (on LE and LYG) induced by the choice of extrapolation distributions, for 2 levels of OS maturity (30% and 50%), as compared to LE and LYG at full maturity. Methods: F

APA, Harvard, Vancouver, ISO, and other styles

35

Dorrer, M. G. "The model of optimal enterprise maturity management in the conditions of noisy source data." Informatization and communication, no. 2 (April 30, 2020): 119–26. http://dx.doi.org/10.34219/2078-8320-2020-11-2-119-126.

Full text

Abstract:

The purpose of this work is to propose a mathematical model of the optimal process for managing the organization›s maturity levels in the presence of interference in the source data. Changes in the organizational maturity of a company are described in terms of linear dynamic management systems. The proposed methodology for optimal management of the organization’s maturity level is demonstrated by the example of evaluating and forecasting the maturity level of one of the departments of a technical university. Baseline data is collected by assessing organizational maturity over several years. Th

APA, Harvard, Vancouver, ISO, and other styles

36

Okuyucu, Aras, and Nilay Yavuz. "Big data maturity models for the public sector: a review of state and organizational level models." Transforming Government: People, Process and Policy 14, no. 4 (2020): 681–99. http://dx.doi.org/10.1108/tg-09-2019-0085.

Full text

Abstract:

Purpose Despite several big data maturity models developed for businesses, assessment of big data maturity in the public sector is an under-explored yet important area. Accordingly, the purpose of this study is to identify the big data maturity models developed specifically for the public sector and evaluate two major big data maturity models in that respect: one at the state level and the other at the organizational level. Design/methodology/approach A literature search is conducted using Web of Science and Google Scholar to determine big data maturity models explicitly addressing big data ad

APA, Harvard, Vancouver, ISO, and other styles

37

Cavique, L., Paulo Pombinho, and Luís Correia. "A Data Science Maturity Model Applied to Students' Modeling." Emerging Science Journal 7, no. 6 (2023): 1976–89. http://dx.doi.org/10.28991/esj-2023-07-06-08.

Full text

Abstract:

Maturity models define a series of levels, each representing an increased complexity in information systems. Data Science appears in the Business Intelligence (BI) and Business Analytics (BA) literature. This work applies the _IABE maturity model, which includes two additional levels: Data Engineering (DE) at the bottom and Business Experimentation (BE) at the top. This study uses the _IABE model for students' modeling in the ModEst project. For this purpose, the Public Administration organism is the Directorate-General for Statistics of Education and Science (DGEEC) of the Portuguese Educatio

APA, Harvard, Vancouver, ISO, and other styles

38

Nesensohn, Claus, David James Bryde, Edward Ochieng, and Damian Fearon. "Maturity and maturity models in lean construction." Construction Economics and Building 14, no. 1 (2014): 45–59. http://dx.doi.org/10.5130/ajceb.v14i1.3641.

Full text

Abstract:

In recent years there has been an increasing interest in maturity models in management-related disciplines; which reflects a growing recognition that becoming more mature and having a model to guide the route to maturity can help organisations in managing major transformational change. Lean Construction (LC) is an increasingly important improvement approach that organisations seek to embed. This study explores how to apply the maturity models to LC. Hence the attitudes, opinions and experiences of key industry informants with high levels of knowledge of LC were investigated. To achieve this, a

APA, Harvard, Vancouver, ISO, and other styles

39

Retrialisca, Fitri, and Umi Chotijah. "The Maturity Measurement of Big Data Adoption in Manufacturing Companies Using the TDWI Maturity Model." Journal of Information Systems Engineering and Business Intelligence 6, no. 1 (2020): 70. http://dx.doi.org/10.20473/jisebi.6.1.70-78.

Full text

Abstract:

Background: Big data technology has been used in several sectors in Indonesia. Adoption of big technology provides great potential for research, especially achievement in the implementation of big data in manufacturing companies. The Data Warehousing Institute (TDWI) Maturity Model is a tool that can be used to measure the state of "As-is" implementation of big data using 5 main dimensions. Maturity level shows the level of organizational ability to adjust big data technology currently.Objective: This study aims to measure the level of maturity in the implementation of big data technology in m

APA, Harvard, Vancouver, ISO, and other styles

40

Perla, Rocco J. "Commentary: Health Systems Must Strive for Data Maturity." American Journal of Medical Quality 28, no. 3 (2012): 263–64. http://dx.doi.org/10.1177/1062860612465000.

Full text

APA, Harvard, Vancouver, ISO, and other styles

41

Ranjbarfard, Mina, and Shahideh Ahmadi. "Data Mining Applications for Banks’ Business Intelligence Maturity." Journal of Digital Information Management 18, no. 5 (2020): 163–72. http://dx.doi.org/10.6025/jdim/2020/18/5-6/163-172.

Full text

APA, Harvard, Vancouver, ISO, and other styles

42

Weber, Christian, Jan Königsberger, Laura Kassner, and Bernhard Mitschang. "M2DDM – A Maturity Model for Data-Driven Manufacturing." Procedia CIRP 63 (2017): 173–78. http://dx.doi.org/10.1016/j.procir.2017.03.309.

Full text

APA, Harvard, Vancouver, ISO, and other styles

43

Thomas, Manoj A., Joseph Cipolla, Bob Lambert, and Lemuria Carter. "Data management maturity assessment of public sector agencies." Government Information Quarterly 36, no. 4 (2019): 101401. http://dx.doi.org/10.1016/j.giq.2019.101401.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

Pathaveerat, Siwalak, Anupun Terdwongworakul, and Artit Phaungsombut. "Multivariate data analysis for classification of pineapple maturity." Journal of Food Engineering 89, no. 2 (2008): 112–18. http://dx.doi.org/10.1016/j.jfoodeng.2008.04.012.

Full text

APA, Harvard, Vancouver, ISO, and other styles

45

Crowston, Kevin, and Jian Qin. "A capability maturity model for scientific data management." Proceedings of the American Society for Information Science and Technology 47, no. 1 (2010): 1–2. http://dx.doi.org/10.1002/meet.14504701359.

Full text

APA, Harvard, Vancouver, ISO, and other styles

46

Podolak, Irene, Oliver Harrison, and Philipp Vetter. "Measuring health data management maturity in Abu Dhabi." Health Policy and Technology 1, no. 3 (2012): 127–36. http://dx.doi.org/10.1016/j.hlpt.2012.07.006.

Full text

APA, Harvard, Vancouver, ISO, and other styles

47

Ofner, Martin, Boris Otto, and Hubert Österle. "A Maturity Model for Enterprise Data Quality Management." Enterprise Modelling and Information Systems Architectures 8, no. 2 (2013): 4–24. http://dx.doi.org/10.1007/s40786-013-0002-z.

Full text

APA, Harvard, Vancouver, ISO, and other styles

48

Sliż, Piotr. "Data Mining Process Maturity – Result of Empirical Research." Problemy Zarządzania - Management Issues 2019, no. 2(82) (2019): 233–51. http://dx.doi.org/10.7172/1644-9584.82.13.

Full text

Abstract:

The main goal of the article is to present the results of the study relating to the assessment of data mining process maturity on the example of Polish organizations. Several partial objectives were added to the main goal. CT1: To diagnose the current state of knowledge regarding the data-mining process in the discipline of management sciences. Attempts at attaining this objective served to identify the knowledge gap. CT2: To adopt an appropriate theoretical perspective in the form of a theoretical model, enabling the implementation of future research challenges. The first section of the artic

APA, Harvard, Vancouver, ISO, and other styles

49

Marttonen Arola, Salla, and David Baglee. "A maturity model for valuable maintenance data management." International Journal of Strategic Engineering Asset Management 4, no. 1 (2023): 1–25. http://dx.doi.org/10.1504/ijseam.2023.10061632.

Full text

APA, Harvard, Vancouver, ISO, and other styles

50

Arola, Salla Marttonen, and David Baglee. "A maturity model for valuable maintenance data management." International Journal of Strategic Engineering Asset Management 4, no. 1 (2023): 1–25. http://dx.doi.org/10.1504/ijseam.2023.136184.

Full text

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!