Abstract In a traditional Business Intelligence (BI) system, power users serve less
experienced casual users. Power users analyze and gather data requested by casual users …

In recent years, Business Intelligence (BI) systems have undergone two distinctly different
fundamental changes. On the one hand, social media systems, machine sensors, devices …

Data Warehouses are the core of the modern systems for decision making. They store
integrated information extracted from various and heterogeneous data sources, making it …

Data profiling comprises a broad range of methods to efficiently analyze a given data set. In
a typical scenario, which mirrors the capabilities of commercial data profiling tools, tables of …

This paper describes the convergence of some of the most influential technologies in the last
few years, namely data warehousing (DW), on-line analytical processing (OLAP), and the …

ABSTRACT Self-service Business Intelligence (SSBI) allows non-technical users to use
Business Intelligence in a self-reliant manner without the support of technical users. Many …

Big Data architectures allow to flexibly store and process heterogeneous data, from multiple
sources, in their original format. The structure of those data, commonly supplied by means of …

Self-service business intelligence and analytics (SSBIA) empowers non-IT users to create
reports and analyses independently. SSBIA methods and processes are discussed in the …

Abstract Multi-model DBMSs (MMDBMSs) have been recently introduced to store and
seamlessly query heterogeneous data (structured, semi-structured, graph-based, etc.) in …

On-Line Analytical Processing (OLAP) tools allow querying large multidimensional
databases called data warehouses (DW). OLAP-style data analysis over the semantic web …