A Framework for Classification of the Data and Information Quality Literature and Preliminart Results (1996-2007)

The value of management decisions, the security of our nation, and the very foundations of our business integrity are all dependent on the quality of data and information. However, the quality of the data and information is dependent on how that data or information will be used. This paper proposes a theory of data quality based on the five principles defined by J. M. Juran for product and service quality and extends Wang et al’s 1995 framework for data quality research. It then examines the data and information quality literature from journals within the context of this framework

Understanding data quality issues in dynamic organisational environments – a literature review

Technology has been the catalyst that has facilitated an explosion of organisational data in terms of its velocity, variety, and volume, resulting in a greater depth and breadth of potentially valuable information, previously unutilised. The variety of data accessible to organisations extends beyond traditional structured data to now encompass previously unobtainable and difficult to analyse unstructured data. In addition to exploiting data, organisations are now facing an even greater challenge of assessing data quality and identifying the impacts of lack of quality. The aim of this research is to contribute to data quality literature, focusing on improving a current understanding of business-related Data Quality (DQ) issues facing organisations. This review builds on existing Information Systems literature, and proposes further research in this area. Our findings confirm that the current literature lags in recognising new types of data and imminent DQ impacts facing organisations in today&rsquo;s dynamic environment of the so-called &ldquo;Big Data&rdquo;. Insights clearly identify the need for further research on DQ, in particular in relation to unstructured data. It also raises questions regarding new DQ impacts and implications for organisations, in their quest to leverage the variety of available data types to provide richer insights.<br /

Understanding Data Quality Issues in Dynamic Organisational Environments : A Literature Review

Technology has been the catalyst that has facilitated an explosion of organisational data in terms of its velocity, variety, and volume, resulting in a greater depth and breadth of potentially valuable information, previously unutilised. The variety of data accessible to organisations extends beyond traditional structured data to now encompass previously unobtainable and difficult to analyse unstructured data. In addition to exploiting data, organisations are now facing an even greater challenge of assessing data quality and identifying the impacts of lack of quality. The aim of this research is to contribute to data quality literature, focusing on improving a current understanding of business-related Data Quality (DQ) issues facing organisations. This review builds on existing Information Systems literature, and proposes further research in this area. Our findings confirm that the current literature lags in recognising new types of data and imminent DQ impacts facing organisations in today’s dynamic environment of the so-called “Big Data”. Insights clearly identify the need for further research on DQ, in particular in relation to unstructured data. It also raises questions regarding new DQ impacts and implications for organisations, in their quest to leverage the variety of available data types to provide richer insights

Robotization and digitalisation in the construction industry

Abstract. Industry 4.0 has emerged as a famous concept in the last few years to describe the significance of digitisation and robotization in the smart manufacturing environment. The advancements in robotics, digital software, and smart technologies have allowed a new wave in the construction industry. The construction industry is the major economic pillar and provides a significant impact on the overall GDP of the country. Despite the predominant pillar, it is considered as the poor innovator and late adopter of new technologies, which ends up with delays and cost overruns in their construction projects. Considering this aspect, the research emphasises the importance of adopting the latest technologies in the construction industry in order to enhance the productivity and efficiency of various processes. This study seeks to examine existing robotization and digitalisation practices in the leading construction companies and intends to provide the required improvement ideas in this research domain. The empirical results revealed that the majority of the case companies lack basis to implement the latest technologies in their construction activities. They believe that effective use of the available technologies is an asset, but it is a long process to be achieved. Thus, the thesis is concluded by providing the critical information regarding the adoption of latest technologies and proposes a framework that can help to enhance the robotization and digitisation practices to improve the performance of the construction activities. The mentioned framework mainly focusses on elements that this research found as a potential need for companies to implement. This framework has a future scope for validation and also key elements of the framework can be utilised for further research