While OLAP has a key role in supporting effective exploration of multidimensional cubes, the
huge number of aggregations and selections that can be operated on data may make the …

This paper structures a novel vision for OLAPby fundamentally redefining several of the
pillars on which OLAP has been based for the last 20 years. We redefine OLAP queries, in …

It is quite common these days for experts, casual analysts, executives and data enthusiasts,
to analyze large datasets through user-friendly interfaces on top of Business Intelligence (BI) …

Abstract Next generation Business Intelligence (BI) systems require integration of
heterogeneous data sources and a strong user-centric orientation. Both needs entail …

Due to their multiple sources and structures, big spatial data require adapted tools to be
efficiently collected, summarized and analyzed. For this purpose, data are archived in data …

Differently from OLTP workloads, OLAP workloads are hardly predictable due to their
inherently extemporary nature. Besides, obtaining real OLAP workloads by monitoring the …

The explosive growth in the amount of data poses challenges in analyzing large data sets
and retrieving relevant information in real-time. This issue has dramatically increased the …

An example method of loading data from a database includes receiving, at a cache node, a
current query and a data chain that includes a sequence of ordered queries. The method …

Publicly accessible data warehouses are an indispensable resource for data analysis.
However, they also pose a significant risk to the privacy of the clients, since a data …

Supporting interactive database exploration (IDE) is a problem that attracts lots of attention
these days. Exploratory OLAP (On-Line Analytical Processing) is an important use case …