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 …

Business Intelligence (BI) solutions require the design and implementation of complex
processes (denoted ETL) that extract, transform, and load data from the sources to a …

Data integration combines information from different sources to provide a comprehensive
view for making informed business decisions. The ETL (Extract, Transform, and Load) …

Business intelligence and data analytics projects often involve low-level, ad hoc data
wrangling and programming, which increases development effort and reduces usability of …

Data warehouses (DW) integrate different data sources in order to give a multidimensional
view of them to the decision-maker. To this aim, the ETL (Extraction, Transformation and …

Extraction, transformation, and loading (ETL) processes are used to extract data from
internal and external sources of an organization, transform these data, and load them into a …

In the current business scenario, real-time analysis of enterprise data through Business
Intelligence (BI) is crucial for supporting operational activities and taking any strategic …

Currently, the blooming growth of social networks such as Facebook, Twitter, Instagram, etc.,
has generated and is still generating a big amount of data, which can be regarded as a gold …

Big Data emerged after a big explosion of data from the Web 2.0, digital sensors, and social
media applications such as Facebook, Twitter, etc. In this constant growth of data, many …

Erroneous or incomplete data generated from various sources can have direct impact in
business analysis. Extracted data from sources need to load into data warehouse after …