The extract, transform, and load (ETL) process is at the core of data warehousing
architectures. As such, the success of data warehouse (DW) projects is essentially based on …

The software processes that facilitate the original loading and the periodic refreshment of the
data warehouse contents are commonly known as Extraction-Transformation-Loading (ETL) …

The growth of the Internet opens up tremendous opportunities for cooperative computation,
where the answer depends on the private inputs of separate entities. Sometimes these …

Business Intelligence (BI) refers to technologies, tools, and practices for collecting,
integrating, analyzing, and presenting large volumes of information to enable better decision …

BACKGROUND: A data warehouse (DW) is an integrated collection of subject-oriented data
in the support of decision making. Importantly, the integration of data sources is achieved …

One of the main tasks in the early stages of a data warehouse project is the identification of
the appropriate transformations and the specification of inter-schema mappings from the …

In this paper, we discuss the state of the art and current trends in designing and optimizing
ETL workflows. We explain the existing techniques for:(1) constructing a conceptual and a …

In order to create better decisions for business analytics, organizations increasingly use
external data, structured, semi-structured and unstructured, in addition to the (mostly …

It is common practice for data providers to include text descriptions for each column when
publishing data sets in the form of data dictionaries. While these documents are useful in …

Decisional systems are crucial for enterprise improvement. They allow the consolidation of
heterogeneous data from distributed enterprise data stores into strategic indicators. An …