Government cloud computing and the policies of data sovereignty

Government cloud services are a new development at the intersection of electronic government and cloud computing which holds the promise of rendering government service delivery more effective and efficient. Cloud services are virtual, dynamic and potentially stateless which has triggered governments' concern about data sovereignty. This paper explores data sovereignty in relation to government cloud services and how national strategies and international policy evolve. It concludes that for countries data sovereignty presents a legal risk which can not be adequately addressed with technology or through contractual arrangements alone. Governments therefore adopt strategies to retain exclusive jurisdiction over government information. --cloud computing,electronic government,data sovereignty,data ownership,information assurance,international data transfers

Digital curation and the cloud

Digital curation involves a wide range of activities, many of which could benefit from cloud deployment to a greater or lesser extent. These range from infrequent, resource-intensive tasks which benefit from the ability to rapidly provision resources to day-to-day collaborative activities which can be facilitated by networked cloud services. Associated benefits are offset by risks such as loss of data or service level, legal and governance incompatibilities and transfer bottlenecks. There is considerable variability across both risks and benefits according to the service and deployment models being adopted and the context in which activities are performed. Some risks, such as legal liabilities, are mitigated by the use of alternative, e.g., private cloud models, but this is typically at the expense of benefits such as resource elasticity and economies of scale. Infrastructure as a Service model may provide a basis on which more specialised software services may be provided. There is considerable work to be done in helping institutions understand the cloud and its associated costs, risks and benefits, and how these compare to their current working methods, in order that the most beneficial uses of cloud technologies may be identified. Specific proposals, echoing recent work coordinated by EPSRC and JISC are the development of advisory, costing and brokering services to facilitate appropriate cloud deployments, the exploration of opportunities for certifying or accrediting cloud preservation providers, and the targeted publicity of outputs from pilot studies to the full range of stakeholders within the curation lifecycle, including data creators and owners, repositories, institutional IT support professionals and senior manager

ERP implementation methodologies and frameworks: a literature review

Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history

Effecting Data Quality Through Data Governance: a Case Study in the Financial Services Industry

One of the most significant challenges faced by senior management today is implementing a data governance program to ensure that data is an asset to an organization\u27s mission. New legislation aligned with continual regulatory oversight, increasing data volume growth, and the desire to improve data quality for decision making are driving forces behind data governance initiatives. Data governance involves reshaping existing processes and the way people view data along with the information technology required to create a consistent, secure and defined processes for handling the quality of an organization\u27s data. In examining attempts to move towards making data an asset in organizations, the term data governance helps to conceptualize the break with existing ad hoc, siloed and improper data management practices. This research considers a case study of large financial services company to examine data governance policies and procedures. It seeks to bring some information to bare on the drivers of data governance, the processes to ensure data quality, the technologies and people involved to aid in the processes as well as the use of data governance in decision making. This research also addresses some core questions surrounding data governance, such as the viability of a golden source record, ownership and responsibilities for data, and the optimum placement of a data governance department. The findings will provide a model for financial services companies hoping to take the initial steps towards better data quality and ultimately a data governance capability

A comparative analysis of good enterprise data management practices:insights from literature and artificial intelligence perspectives for business efficiency and effectiveness

Abstract. This thesis presents a comparative analysis of enterprise data management practices based on literature and artificial intelligence (AI) perspectives, focusing on their impact on data quality, business efficiency, and effectiveness. It employs a systematic research methodology comprising of a literature review, an AI-based examination of current practices using ChatGPT, and a comparative analysis of findings. The study highlights the importance of robust data governance, high data quality, data integration, and security, alongside the transformative potential of AI. The limitations revolve around the primarily qualitative nature of the study and potential restrictions in the generalizability of the findings. However, the thesis offers valuable insights and recommendations for enterprises to optimize their data management strategies, underscoring the enhancement potential of AI in traditional practices. The research contributes to scientific discourse in information systems, data science, and business management