A Step Foreword Historical Data Governance in Information Systems

2019 ◽  
pp. 80-90
Author(s):  
José Pedro Simão ◽  
Orlando Belo
Keyword(s):  
Information Systems ◽  
Historical Data ◽  
Data Governance

Challenges of Data Management in Always-On Enterprise Information Systems

2010 ◽  
pp. 443-462
Author(s):  
Mladen Varga
Keyword(s):  
Information Systems ◽  
Data Management ◽  
Data Privacy ◽  
Data Governance ◽  
Enterprise Information ◽  
Enterprise Information Systems ◽  
Degradation Data ◽  
Association Data ◽  
Data Continuity ◽  
Integration Data

Data management in always-on enterprise information systems is an important function that must be governed, that is, planned, supervised, and controlled. According to Data Management Association, data management is the development, execution, and supervision of plans, policies, programs, and practices that control, protect, deliver, and enhance the value of data and information assets. The challenges of successful data management are numerous and vary from technological to conceptual and managerial. The purpose of this chapter is to consider some of the most challenging aspects of data management, whether they are classified as data continuity aspects (e.g., data availability, data protection, data integrity, data security), data improvement aspects (e.g., coping with data overload and data degradation, data integration, data quality, data ownership/stewardship, data privacy, data visualization) or data management aspect (e.g., data governance), and to consider the means of taking care of them.

Challenges of Data Management in Always-On Enterprise Information Systems

2011 ◽  
pp. 1695-1714 ◽  
Author(s):  
Mladen Varga
Keyword(s):  
Information Systems ◽  
Data Management ◽  
Data Privacy ◽  
Data Governance ◽  
Enterprise Information ◽  
Enterprise Information Systems ◽  
Degradation Data ◽  
Association Data ◽  
Data Continuity ◽  
Integration Data

Data management in always-on enterprise information systems is an important function that must be governed, that is, planned, supervised, and controlled. According to Data Management Association, data management is the development, execution, and supervision of plans, policies, programs, and practices that control, protect, deliver, and enhance the value of data and information assets. The challenges of successful data management are numerous and vary from technological to conceptual and managerial. The purpose of this chapter is to consider some of the most challenging aspects of data management, whether they are classified as data continuity aspects (e.g., data availability, data protection, data integrity, data security), data improvement aspects (e.g., coping with data overload and data degradation, data integration, data quality, data ownership/stewardship, data privacy, data visualization) or data management aspect (e.g., data governance), and to consider the means of taking care of them.

Master Data-Supply Chain Management, the Key Lever for Collaborative and Compliant Partnerships in Big Data Era

2021 ◽  
pp. 72-101
Author(s):  
Samia Chehbi Gamoura ◽  
Manisha Malhotra
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Information Systems ◽  
Data Governance ◽  
Traditional Management ◽  
Logistics Networks ◽  
Master Data ◽  
Hands On ◽  
Master Data Management

With the advent of big data in supply chain information systems (SCIS), data compliance and consistency are becoming vital. Today, SC stakeholders need to pay more attention to data governance, which requires changing traditional management methods. These can be achieved by mastering a single repository through what is usually named master data management (MDM). However, accomplishing this objective is particularly challenging in the complex logistics networks of supply chains (SC). The volatile nature of the logistics flows that increase exponentially because of the facilitation of exchanges' interoperability in the information systems. In this chapter, the authors propose an MDM-based framework for the supply chain information systems as an enabler for strong collaboration and compliance. For proof of concept, a case study of a French hypermarket is examined through benchmarking scenarios. The outcomes of the case validate our approach as a hands-on solution when applied correctly. Finally, the chapter discusses the key findings and the limitations of our framework.

The Future of Aircraft Feedback Information: Maintainability Allocation Methodology

2014 ◽  
Vol 629 ◽  
pp. 225-230
Author(s):  
Wan Mohd Sufian Wan Husain
Keyword(s):  
Information Systems ◽  
Reporting System ◽  
Historical Data ◽  
Importance Measure ◽  
Aircraft Maintenance ◽  
Feedback Information ◽  
Design Improvement ◽  
Future Improvement ◽  
Design Activities ◽  
Types Of Information

In this paper, the author looks at certain areas of maintainability prediction process where missteps or misapplications most commonly occur. This research attempts to utilise the aircraft maintenance historical data and information (i.e. feedback information systems). Aircraft feedback information such as Service Difficulty Reporting System (SDRS) and Air Accidents Investigation Branch (AAIB) contains various types of information that could be used for future improvement rather than just the failure elements, as well as to help identify the critical and sensitive components that need more attention for further improvement. The study shows that the aircraft maintenance related feedback information systems analyses are very useful for deciding the maintainability effectiveness; these include planning, organizing maintenance and design improvement. There is no doubt that historical data information has the ability to contribute an important role in design activities. The results also show that maintainability is an importance measure that can be used as a guideline for managing efforts made for the improvement of aircraft components.

scholarly journals PERAN SISTEM INFORMASI GEOGRAFI (SIG) SEBAGAI ALAT ANALISIS DALAM ILMU

2019 ◽  
Vol 25 (1) ◽  
pp. 13-21
Author(s):  
Imam Arifa'illah Syaiful Huda
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Cultural Heritage ◽  
Historical Data ◽  
Descriptive Analysis ◽  
Geographic Information ◽  
Spatial Form ◽  
The Past ◽  
Science Of History

Geographic information systems have an important role in the science of history. Geographic information systems are able to integrate various data in the study of history, combine, analyze, and map the results. This journal aims to examine the role of geographic information systems in geography. The method used is descriptive analysis method. The process of searching, collecting, and analyzing data is done by using literature studies from various reliable sources, such as books, journals, scientific articles, and academic archives and taking data on the distribution of cultural heritage in the City of Jambi. The results of the analysis show that the role of geographic information systems in the history of science as a tool to improve spatial or spatial analysis. in detail, the role of geographic information systems in the study of historical science can 1) provide historical data in a spatial form in maps, such as the map of the distribution of cultural heritage in Jambi City, 2) be able to see the comparison of historical facts from several regions, 3) make it easy to associate and correlating with the surrounding environment, 4) regionalization can be made related to the area of ​​power in the past, 5) makes it easy to answer the question "where" and "why there. And understand the relationship between humans and the environment, and how they affect the dynamics of life in the past. Thus, the role of GIS as an analytical tool in history is very important because it is able to provide data spatially and deepen the analysis of historical data.

Maintainability Prediction for Aircraft Mechanical Components Utilizing Aircraft Feedback Information

2012 ◽  
Vol 225 ◽  
pp. 528-533 ◽  
Author(s):  
Wan Mohd Sufian Wan Husain
Keyword(s):  
Information Systems ◽  
Historical Data ◽  
Aircraft Design ◽  
Importance Measure ◽  
Aircraft Maintenance ◽  
Feedback Information ◽  
Design Improvement ◽  
Future Improvement ◽  
Design Activities ◽  
Types Of Information

This paper attempts to utilise aircraft maintenance historical data and information for future aircraft design from the perspective of maintanability. Aircraft feedback information contains various types of information that could be used for future improvement rather than just the failure elements. The study shows that the aircraft maintenance related feedback information systems analyses were very useful for deciding maintainability effectiveness; these include planning, organising maintenance and design improvement. There is no doubt that historical data information has the ability to contribute with an important role in design activities. The results also show that maintainability is an importance measure that can be used as a guideline for managing efforts made for the improvement of aircraft components.

scholarly journals A call to strengthen data in response to COVID-19 and beyond

2020 ◽  
Author(s):  
Natasha Azzopardi-Muscat ◽  
Hans Henri P Kluge ◽  
Samira Asma ◽  
David Novillo-Ortiz
Keyword(s):  
Information Systems ◽  
Health Information Systems ◽  
Health Data ◽  
Coordination Mechanism ◽  
Data Driven ◽  
National Data ◽  
Data Governance ◽  
Monitoring And Forecasting ◽  
Data Culture ◽  
Political Decisions

Abstract The COVID-19 (coronavirus disease 2019) pandemic has underscored the critical need for all countries to strengthen their health data and information systems and ensure the routes the data travel, from submission to use, are unobstructed. Timely, credible, reliable, and actionable data are key to ensuring that political decisions are data driven and facilitate understanding, monitoring, and forecasting. To ensure that critical decisions related to the wider health and socioeconomic effects of this pandemic are data driven, each country needs to develop or enhance a national data governance plan that includes a clear coordination mechanism, well-defined and documented data processes (manual or electronic), the exchange of data, and a data culture to empower users. In addition, countries should now more than ever invest and enhance their data and health information systems to ensure that all decisions are data driven and that they are prepared for what is next.

Challenges of Data Management in Always-On Enterprise Information Systems

2010 ◽  
pp. 109-128 ◽  
Author(s):  
Mladen Varga
Keyword(s):  
Information Systems ◽  
Data Management ◽  
Data Privacy ◽  
Data Governance ◽  
Enterprise Information ◽  
Enterprise Information Systems ◽  
Degradation Data ◽  
Association Data ◽  
Data Continuity ◽  
Integration Data

Data management in always-on enterprise information systems is an important function that must be governed, that is, planned, supervised, and controlled. According to Data Management Association, data management is the development, execution, and supervision of plans, policies, programs, and practices that control, protect, deliver, and enhance the value of data and information assets. The challenges of successful data management are numerous and vary from technological to conceptual and managerial. The purpose of this chapter is to consider some of the most challenging aspects of data management, whether they are classified as data continuity aspects (e.g., data availability, data protection, data integrity, data security), data improvement aspects (e.g., coping with data overload and data degradation, data integration, data quality, data ownership/stewardship, data privacy, data visualization) or data management aspect (e.g., data governance), and to consider the means of taking care of them.

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