The Extract-Transform-Load (ETL) process in data warehousing involves extracting data
from source databases, transforming it into a form suitable for research and analysis, and …

Enterprises use data warehouses to accumulate data from multiple sources for data analysis
and research. Since organizational decisions are often made based on the data stored in a …

The test pyramid is a conceptual model that describes how quality checks can be organized
to ensure coverage of all components of a system, at all scales. Originally conceived to help …

In order to properly test software, test data of a certain quality is needed. However, useful
test data is often unavailable because existing or hand-crafted data might not be diverse …

In the past few years, the data warehouse (DW) has regained experts' interest due to the
paradigm shift from data storages to data analysis. During the development of DWs data …

A data warehouse should be tested for data quality on regular basis, preferably as a part of
each ETL cycle. That way, a certain degree of confidence in the data warehouse reports can …

Business Intelligence (BI) relies on Data Warehouse (DW), a historical data repository
designed to support the decision making process. Despite the potential benefits of a DW …

This paper presents an approach to automate the selection and execution of previously
indentified test cases for loading procedures in Business Intelligence (BI) environments …

Le processus de conception des BD ne cesse d'augmenter en complexité et d'exiger plus de
temps et de ressources afin de contenir la diversité des applications BD. Rappelons qu'il se …

MLOps is becoming a widespread practice in modern machine learning and data science.
The word” MLOps” combines machine learning technology and business operation process …