Clouds Ahead – The Transformation of Vehicle Development and Data Management Processes

2021 ◽  
pp. 183-194
Author(s):  
Gerhard Niederbrucker ◽  
Albrecht Pfaff ◽  
Christian Donn ◽  
Michael Kochem
Keyword(s):  
Data Management ◽  
Vehicle Development ◽  
Management Processes

Lessons Learned from Usace Seepage Barrier Wall Construction: Wolf Creek To Present

2018 ◽  
Vol 24 (1) ◽  
pp. 75-88 ◽  
Author(s):  
Georgette Hlepas ◽  
Vanessa Bateman
Keyword(s):  
Data Management ◽  
Continuous Improvement ◽  
Lessons Learned ◽  
Army Corps ◽  
Army Corps Of Engineers ◽  
Management Processes ◽  
Verification Methods ◽  
Efficiency And Effectiveness ◽  
Wall Construction ◽  
Barrier Wall

Abstract The U.S. Army Corps of Engineers (USACE) maintains a lessons-learned goal for all major projects to capture knowledge gained. The focus of the formal lessons-learned process is to share knowledge and experience nationwide improving USACE contracting methodologies, reducing overall costs, and improving designs. This continuous improvement can be seen in the evolution of USACE barrier wall construction designs and contracting methods. From the first Wolf Creek Dam barrier wall installed in the 1970s to the more recent Bolivar and East Branch Dam barrier wall projects, documentation and sharing of lessons learned in areas such as grouting, data management, and quality assurance procedures have increased the efficiency and effectiveness of barrier wall designs, monitoring, and contract specifications. Contractual philosophy, use of pre-grouting treatment, verification methods, and data management processes have all changed due to lessons learned and have enabled the USACE to improve the overall end product of barrier wall projects.

scholarly journals Intelligent Data Management and Security in Cloud Computing

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3458
Author(s):  
Lidia Ogiela ◽  
Marek R. Ogiela ◽  
Hoon Ko
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Service Management ◽  
Secret Data ◽  
Data Services ◽  
New Class ◽  
Management Processes ◽  
Confidential Data ◽  
Shared Secret ◽  
Linguistic Methods

This paper will present the authors’ own techniques of secret data management and protection, with particular attention paid to techniques securing data services. Among the solutions discussed, there will be information-sharing protocols dedicated to the tasks of secret (confidential) data sharing. Such solutions will be presented in an algorithmic form, aimed at solving the tasks of protecting and securing data against unauthorized acquisition. Data-sharing protocols will execute the tasks of securing a special type of information, i.e., data services. The area of data protection will be defined for various levels, within which will be executed the tasks of data management and protection. The authors’ solution concerning securing data with the use of cryptographic threshold techniques used to split the secret among a specified group of secret trustees, simultaneously enhanced by the application of linguistic methods of description of the shared secret, forms a new class of protocols, i.e., intelligent linguistic threshold schemes. The solutions presented in this paper referring to the service management and securing will be dedicated to various levels of data management. These levels could be differentiated both in the structure of a given entity and in its environment. There is a special example thereof, i.e., the cloud management processes. These will also be subject to the assessment of feasibility of application of the discussed protocols in these areas. Presented solutions will be based on the application of an innovative approach, in which we can use a special formal graph for the creation of a secret representation, which can then be divided and transmitted over a distributed network.

Big Data and Advance Analytics: Architecture, Techniques, Applications, and Challenges

2017 ◽  
Vol 4 (4) ◽  
pp. 21-47 ◽  
Author(s):  
Surabhi Verma
Keyword(s):  
Big Data ◽  
Data Management ◽  
Big Data Analytics ◽  
Competitive Advantages ◽  
Organizational Goals ◽  
Current State ◽  
Management Processes ◽  
Using Data ◽  
Tools And Techniques ◽  
Different Characteristics

The insights that firms gain from big data analytics (BDA) in real time is used to direct, automate and optimize the decision making to successfully achieve their organizational goals. Data management (DM) and advance analytics (AA) tools and techniques are some of the key contributors to making BDA possible. This paper aims to investigate the characteristics of BD, processes of data management, AA techniques, applications across sectors and issues that are related to their effective implementation and management within broader context of BDA. A range of recently published literature on the characteristics of BD, DM processes, AA techniques are reviewed to explore their current state, applications, issues and challenges learned from their practice. The finding discusses different characteristics of BD, a framework for BDA using data management processes and AA techniques. It also discusses the opportunities/applications and challenges managers dealing with these technologies face for gaining competitive advantages in businesses. The study findings are intended to assist academicians and managers in effectively quantifying the data available in an organization into BD by understanding its properties, understanding the emerging technologies, applications and issues behind BDA implementation.

scholarly journals The Long Term Affects Of Data Management On The Economic Welfare Of A City Government

2011 ◽  
Vol 4 (5) ◽  
pp. 13
Author(s):  
Donald A. Forrer
Keyword(s):  
Data Management ◽  
Development Process ◽  
Public Debate ◽  
City Government ◽  
Economic Welfare ◽  
Critical Areas ◽  
Management Processes ◽  
The City

This research examines management processes that lead to the omission of $2.3 million in betterment fees in the City of Cape Coral (City). It concentrates on management processes, data problems, and personnel issues that contributed and resulted in developing properties completing the Planned Development Process (PDP) without checks from critical areas in the financial system. This research analyzes how betterment fees, often called Contribution in Aid of Construction (CIAC), were designed, collected, and managed. This case study also outlines key measurement processes neglected by the City and demonstrates how management corrected the issue of lost revenue through errant billing by analysis and reengineering of the system. Despite hours of public debate and input from concerned citizens, this issue has continued for approximately 10 years. A 2004 betterment list is substantially increased and contains some properties listed on the original 1996 list. The issue is still as controversial as ever and efforts to address it seem to be ignored or minimized.

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