. Data Quality.
It is very difficult to say what data quality means. The word quality itself has different meanings for different people. Even for an individual the word may has a different meaning regarding the circumstances. I will use an example to try to make it clearer. If we ask three people to tell us which car they believe is a quality purchase, we will get three or even more different opinions. Some people will say that acceleration matters, others will say security. Some would prefer an environment friendly car, others a low price one. This is the reason why there is not a universally agreement of what data quality means, so quite few definitions exist. In my opinion Joseph Moses Juran’s definition is the most representative and summarizes the most of the existing definitions. According to Joseph Moses Juran “Data are of high quality if they are fit to their intended uses in operations, decision making and planning” [1].
So how we know if our data are of good or bad quality? Following the car example, in order to answer this question we have to define which characteristics we should take into consideration and how much each of them weights. It is also important these characteristics to be measurable. A continuous research in this field providing us a great range of data attributes along with a ranking, according to their importance. In data quality literature these attributes referred as dimensions. From now on we will use this term when we talk about data quality characteristics. In chapter 2.2 we will present the data quality dimensions in detailed.
2.1 Why good data quality is critical.
Back in 2006, Clive Humby a mathematician from Sheffield said that “Data is the new oil”, in an attempt to highlight the signific...
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...such as the “heterogeneity of their components” and security issues.
d. Cooperative IS. According to Massimo Mecella et al. “is a large scale information system that interconnects various systems of different and autonomous organizations, sharing common objectives” [30]. The main problems with these information systems are the many copies of the same objects (duplicate copies) and the possibility of poor data quality from one source to spread through the cooperative systems. Thus it is very important for the individual information systems to be trusted.
e. Web IS. The importance of web led the classical information systems to transform in order to integrate with web technologies. This means that a web application can access an organization’s dataset. And as we mentioned above, this integration creates new data issues, like security and accessibility.
f. P2P IS.
According to Merriam-Webster, quality is defined as how good or bad something is. This applies to all things such as a computer, food, and even life. However, Pirsig goes beyond the superficial and explores the true meaning of Quality.
One of the biggest problems that affect everyone is data aggregation. The more the technology develop, the powerful and dangerous it gets. Today there are many companies that aggregate a lot of information about us. Those companies gathering our data from different sources, which create a detailed record about us. Since all services have been computerized whether it is handled directly or indirectly through computers, there is no way to hide your information. We used computers, because they are faster, better, and accurate more that any human being. It solved many problems; however, it created new ones. Data does not means anything if it stands alone, because it is only recoded facts and figure, yet when it organized and sorted, it become information. These transformed information. Data aggregation raises many questions such as, who is benefiting from data aggregation? What is the impact on us (the users)? In this paper I will discuses data aggregation and the ethics and legal issues that affect us.
quality we can predicate from it. The systems that fail are those who rely on
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