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Defect Analytics: OLAP for Delivery Excellence
2009
International Conference on Management of Data
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Defect Analytics uses OLAP on a defects repository to produce actionable insights that cannot be obtained from the standard reports generated through a defect tracking system. ...
In this paper, we develop the idea of Defect Analytics and present examples to illustrate its significance along with some initial work we have done to translate these concepts into a tool. ...
(Data Warehousing, OLAP) in an even-more established process (defect logging and tracking). ...
dblp:conf/comad/MallyaR09
fatcat:4l3chte3ovgq3j2uhrtb6doybi
Reducing defects in IT service delivery
2013
Proceedings of 2013 IEEE International Conference on Service Operations and Logistics, and Informatics
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In IT Service Delivery organizations, Quality Analysts (QAs) are responsible for analyzing sets of service tickets to detect exceptional trends, launch investigations and identify and remove defects in ...
be triggered to reduce defects. ...
For some of the other key analytics requiring manipulation on text attributes, the capability might not even be there in Excel, or require inordinately long time and manual effort -for example, assigning ...
doi:10.1109/soli.2013.6611373
fatcat:thnmp23dcfgxhnfwp2o6oomtgm
An Improvement in Defect Detection Efficiency -A Review
2016
Indian Journal of Science and Technology
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In memory analytics can be employed for Defect classification. This method provides effectiveness of defect classification and rates defect as low, high and medium. ...
Methods and Statistical Analysis:-Agile methodology, with In-memory analytics is employed to improve the effectiveness of defect detection efficiency. ...
This analytics provides analysis of the defect and also rate the defects. Hence provide excellent decision for the Designer to speed up in identifying the defect and rectify it. ...
doi:10.17485/ijst/2016/v9i45/106490
fatcat:2e7rkfetdbf7foeebc6meuezfq
A knowledge‐based system to support procurement decision
2005
Journal of Knowledge Management
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Design/methodology/approach -The proposed system encompasses hybrid artificial intelligence (AI) technologies, Online analytical processing (OLAP) applications and neural networks. ...
Recognizes the void of research in the infrastructure of the hybrid AI technologies for knowledge discovery. ...
The OLAP module evaluates the vendor based on six assessment factors: (1) Product type. (2) Product methodology. (3) Materials. (4) Production cost. (5) Delivery time. (6) Defect rate. ...
doi:10.1108/13673270510582983
fatcat:vvdqsicsbraynotubu7l5s625y
An Analytics Environment Architecture for Industrial Cyber-Physical Systems Big Data Solutions
2021
Sensors
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An architectural design reference for a Big Data analytics architecture is proposed. ...
The goal of this paper is to support the design of analytics Big Data solutions for iCPS for the modeling of data elements, predictive analysis, inference of the key performance indicators, and real-time ...
Therefore, a significant amount of fault monitoring through log data, if available, can provide excellent information for data-based diagnostics. ...
doi:10.3390/s21134282
pmid:34201541
fatcat:vmoo3gfvd5ay5mlysrz6kdfwwa
Big Data Analytics and Its Applications in Supply Chain Management
[chapter]
2020
New Trends in the Use of Artificial Intelligence for the Industry 4.0
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BDA provides a tool for extracting valuable patterns and information in large volume of data. ...
Big data analytics capability (BDA) is one of the best techniques, which can help organizations to overcome their problem. ...
processing (OLAP) system are used and supported by reporting technology (e.g. ...
doi:10.5772/intechopen.89426
fatcat:e6vsgfegfrd7redxplv54ofdku
The Art of Data Science and Big Data Analytics: Inspecting and Transforming Data
2020
Asian Journal of Managerial Science
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challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for ...
and its characteristics , data structures, data analytics life cycle, emphasizes critical points on these issues. ...
Implicit analytics focuses on deep analytics, typically by predictive modeling, optimization, prescriptive analytics, and actionable knowledge delivery. ...
doi:10.51983/ajes-2020.9.1.2374
fatcat:254ckl32lfdw7aohkdswec7r3i
The Art of Data Science and Big Data Analytics: Inspecting and Transforming Data
2020
Asian Journal of Computer Science and Technology
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challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for ...
and its characteristics , data structures, data analytics life cycle, emphasizes critical points on these issues. ...
Implicit analytics focuses on deep analytics, typically by predictive modeling, optimization, prescriptive analytics, and actionable knowledge delivery. ...
doi:10.51983/ajcst-2020.9.1.2151
fatcat:yo2t2u5ohfbetivgqkjm4kwqbu
The role of reverse logistics in the transition to a circular economy: Case study of automotive spare parts logistics
Uloga obrnute logistike kod prelaska na cirkularnu ekonomiju - studija slučaja logistike rezervnih automobilskih delova
2021
FME Transaction
Uloga obrnute logistike kod prelaska na cirkularnu ekonomiju - studija slučaja logistike rezervnih automobilskih delova
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For this purpose, an information system was developed. ...
conditions and vehicle subsystems, were introduced for the first time. ...
For implementation of OLAP cube the hybrid option has been chosen. Hybrid OLAP is a combination of both ROLAP (Relational OLAP) and MOLAP (Multidimensional OLAP). ...
doi:10.5937/fme2101173m
fatcat:2hsn5vykpragxbqriy3pc2utnu
Business Analytics in the Context of Big Data: A Roadmap for Research
2015
Communications of the Association for Information Systems
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We bridge the gap between academic and practitioner research by presenting a big data analytics framework that depicts a process view of the components needed for big data analytics in organizations. ...
Recognizing the potential of "big data" to offer new insights for decision making and innovation, panelists at the two events discussed how organizations can use and manage big data for competitive advantage ...
In his tutorial on big data analytics, Watson (2014 Watson ( , p. 1264 states that some organizations are creating "analytics centers of excellence" for providing strategic direction for big data analytics ...
doi:10.17705/1cais.03723
fatcat:sxcf7lmw4raxrm4zzeuaogpmf4
THE NECESSITY OF INFORMATION QUALITY FOR EFFECTIVE BUSINESS INTELLIGENCE
2012
South African Journal of Industrial Engineering
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Some of the differences between OLTP (On-line transactional processing) and OLAP (On-line analytical processing) are given in Table 1 . ...
Even though the same relational database technology can be used for both OLTP and OLAP systems by using different data model structures, some OLAP systems run on multidimensional database technology. ...
doi:10.7166/17-1-162
fatcat:wp64v2dhwjfofd37zjylbxgcvm
Business Intelligence and Big Data in Higher Education: Status of a Multi-Year Model Curriculum Development Effort for Business School Undergraduates, MS Graduates, and MBAs
2015
Communications of the Association for Information Systems
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It also addresses ethical issues in the management of customer data, enterprise-level support for experimentation-based innovation, and embedding analytics in business processes and managing enterprise ...
The course reinforces the role of decision support for sound personal decision making strategies and for creating and maintaining an enterprise-level culture of evidence/fact-based decision making. ...
ACKNOWLEDGMENTS We sincerely thank TUN's board and members for their support of this project as part of the TUN BI curriculum committee initiative. ...
doi:10.17705/1cais.03623
fatcat:gkiduqj5gra3pluhjo2jlorvgu
Development of a co-operative distributed process mining system for quality assurance
2008
International Journal of Production Research
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This method incorporates the concept of data mining and knowledge refinement into decision making process for ensuring "doing the right things" within the workflow. ...
In this paper, a co-operative distributed process mining system (CDPMS) is developed to streamline the workflow along the supply chain in order to offer shorter delivery times, more flexibility and higher ...
Acknowledgements The authors wish to thank the Research Office of the Hong Kong Polytechnic University for the support of this research project. ...
doi:10.1080/00207540701441939
fatcat:fe6blm6nm5gypicamnqnofkgoa
Ten years of preanalytical monitoring and control: Synthetic Balanced Score Card Indicator
2015
Biochemia Medica
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Preanalytical control and monitoring continue to be an important issue for clinical laboratory professionals. ...
The aim of the study was to evaluate a monitoring system of preanalytical errors regarding not suitable samples for analysis, based on different indicators; to compare such indicators in different phlebotomy ...
Acknowledgements The authors wish to thank all the laboratory staff, for its excellent delivery of laboratory services and special thanks to English teacher, Caroline Dale. ...
doi:10.11613/bm.2015.005
pmid:25672466
pmcid:PMC4401317
fatcat:xg4ja3kqlvfvrou2fnfja3ntdi
Intelligent tools and techniques for modern management
2009
Chinese Business Review
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Examples include decision support systems, executive information systems, online-analytical processing (OLAP), data warehouses and data mining systems. ...
Therefore, the terms of the search vector representing technical metadata of an OLAP report (reference objects and ratios) can be selected for an initial definition of a new OLAP report. ...
doi:10.17265/1537-1506/2009.02.007
fatcat:gmreacga35davgqfeh36hnifs4
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