Data cleaning and ETL processes are usually modeled as graphs of data transformations. The involvement of the users responsible for executing these graphs over real data is importa...
The problem of data cleaning, which consists of removing inconsistencies and errors from original data sets, is well known in the area of decision support systems and data warehou...
Helena Galhardas, Daniela Florescu, Dennis Shasha,...
Cleaning data of errors in structure and content is important for data warehousing and integration. Current solutions for data cleaning involve many iterations of data “auditing...
Data cleaning deals with the detection and removal of errors and inconsistencies in data, gathered from distributed sources. This process is essential for drawing correct conclusio...
Hamid Haidarian Shahri, Ahmad Abdollahzadeh Barfor...
Data ambiguity is inherent in applications such as data integration, location-based services, and sensor monitoring. In many situations, it is possible to “clean”, or remove, ...
Reynold Cheng, Eric Lo, Xuan Yang, Ming-Hay Luk, X...