Extract, Transform and Load (ETL) processes are widely used in Data Warehousing in order to extract, cleanse and load data into a centralized location for better analysis and decision-making. As users become more demanding for on-line decision making, ETL processes grow large and more complex. Most processes are deployed at the physical level without any abstraction, thus costs of maintenance a...

Data Warehouses (DWs) are repositories which contain the unified history of an enterprise for decision support. The data must be Extracted from information sources, Transformed and integrated to be Loaded (ETL) into the DW, using ETL tools. These tools focus on data movement, where the models are only used as a means to this aim. Under a conceptual viewpoint, the authors want to innovate the ET...

Testing is one of the key factors to any software products’ success and data warehouse systems are no exception. Data warehouse can be tested in different ways (e.g. front-end testing, database testing) but testing the data warehouse’s ETL procedures (sometimes called back-end testing [1]) is probably the most complex and critical data warehouse testing job, because it directly affects the qual...

The data warehouse (DW) system design involves several tasks such as defining the DW schemas and the ETL processes specifications, and these have been extensively studied and practiced for many years. The problems in heterogeneous data integration are still far from being resolved due to the complexity of ETL processes and the fundamental problems of data conflicts in information sharing enviro...

Using differential display of rat fetal and postnatal cardiomyocytes, we have identified a novel seven-transmembrane receptor, ETL. The cDNA-predicted amino acid sequence of ETL indicated that it encodes a 738-aa protein composed of a large extracellular domain with epidermal growth factor (EGF)-like repeats, a seven-transmembrane domain, and a short cytoplasmic tail. ETL belongs to the secreti...

Extraction-Transformation-Loading (ETL) tools are pieces of software responsible for the extraction of data from several sources, their cleansing, customization and insertion into a data warehouse. Usually, these processes must be completed in a certain time window; thus, it is necessary to optimize their execution time. In this paper, we delve into the logical optimization of ETL processes, mo...

The design of an Extract – Transform – Load (ETL) workflow for the population of a Data Warehouse is a complex and challenging procedure. In previous work, we have presented an ontology-based approach to facilitate the conceptual design of an ETL scenario. In this paper, we elaborate on this work, by investigating the application of Natural Language (NL) techniques to the ETL environment and we...

Data mining is the process of extracting non-trivial patterns from large volumes of data. It generates insight and turns the data into valuable information. A critical yet common flaw when performing data mining is to disregard the geographic origin of the data. When this geospatial attribute is taken into consideration, the process is called geospatial data mining. This task essentially deals ...

We present a new ensemble method that uses Entropy Guided Transformation Learning (ETL) as the base learner. The proposed approach, ETL Committee, combines the main ideas of Bagging and Random Subspaces. We also propose a strategy to include redundancy in transformation-based models. To evaluate the effectiveness of the ensemble method, we apply it to three Natural Language Processing tasks: Te...