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 …

In malicious URLs detection, traditional classifiers are challenged because the data volume
is huge, patterns are changing over time, and the correlations among features are …

Since the late 1970s, relational database technology has been adopted by most
organizations to store their essential data. However, nowadays, the needs of these …

The dynamicity of RDF data has motivated the development of solutions for archiving, ie, the
task of storing and querying previous versions of an RDF dataset. Querying the history of a …

Abstract The use of Semantic Web and linked data increases the possibility of data
accessibility, interpretability, and interoperability. It supports cross‐domain data and …

Organization with considerable investment into data warehousing, the influx of various data
types and forms requires certain ways of prep** data and staging platform that support …

Big data and geographic information systems (GIS) are two technologies that have
increasingly influenced many areas in the last 10 years and will continue to improve and …

ABSTRAK PT Food Station merupakan Badan Usaha Milik Daerah milik Pemprov DKI yang
berfungsi antara lain mengelola pusat perdagangan beras antar daerah dan antar pulau …

Digital transformation of a railway system based on big data technologies relies on
integrating large volumes of streaming data into digitally enabled enterprise systems to form …

Many industries and academia have devoted a lot of effort and money to creating and/or
using good extract-transform-load (ETL) software suitable for their data analysis purposes …