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 amount of available data is continuously growing. This phenomenon promotes a new
concept, named big data. The highlight technologies related to big data are cloud computing …

Data warehousing has been indispensable to enterprises for decades. However,
infrequently updated data warehouse environment does not support quicker business …

Recently, the use of NoSQL databases has grown to manage unstructured data for
applications to ensure performance and scalability. However, many organizations prefer to …

Over the past decade, digital transformation has led to the evolution of databases towards
Big Data. A need to collect and analyze data from different sources has emerged. At the …

ETL is the bedrock of a data warehouse. As the data accelerates in the diversified fields, it is
substantive to integrate the data to extract the prerequisites for business advancement and …

The development of analytical systems imposes several challenges related not only to the
amount and heterogeneity of the involved data but also to the constant need to readapt and …

With the explosion of new data processing and storage technologies nowadays, businesses
are looking to harness the hidden value of data, each in their own way. Many contributions …

NoSQL stores have become ubiquitous since they offer a new cost-effective and schema-
free system. Although NoSQL systems are widely accepted today, Business Intelligence & …

These days, NoSQL (Not only SQL) databases are being used as a deployment tool for Data
Warehouses (DW) due to its support for dynamic and scalable data modeling capabilities …