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 …

Data warehouse (DW) are used in local or global level as per usages. Most of the DW was
designed for online purposes targeting the multinational firms. Majority of local firms directly …

The metadata system is the key system for sharing and transforming data between various
information systems (IS), and each database system has its own structure for storing and …

The application of process mining techniques for analyzing customer journeys seems
promising for different stakeholders in the tourism domain, ie, the tourism providers are …

Satellite image time series (SITS) is a challenging domain for knowledge discovery
database due to their characteristics: each image has several sunspots and each sunspot is …

Social data warehouse (SDW) combines corporate data with user-generated content (UGC)
to improve decision maker analysis. UGC data are heterogeneous, unstructured and …

Analyzing social networks data becomes increasingly important for many companies day-to-
day operations. However, due to their scale, complexity and dynamics, these networks are …

The most effective method to improve information system capabilities is to enable instant
access to several relational database sources and transform data with a logical structure into …

Abstract Extraction-Transformation-Loading (ETL) tools are pieces of software responsible
for the extraction of data from heterogeneous sources, their cleansing, customization and …

The information systems that support small, medium, and large organisations need data
transformation solutions from multiple data sources to fulfill the requirements of new …