Self-service business intelligence is about enabling non-expert users to make well-informed
decisions by enriching the decision process with situational data, ie, data that have a narrow …

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 …

OLAP queries are not normally formulated in isolation, but in the form of sequences called
OLAP sessions. Recognizing that two OLAP sessions are similar would be useful for …

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 Information flooding may occur during an OLAP session when the user drills down
her cube up to a very fine-grained level, because the huge number of facts returned makes it …

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

Many scientific databases nowadays are publicly available for querying and advanced data
analytics. One prominent example is the Sloan Digital Sky Survey (SDSS)—SkyServer …

Decision-makers, whether at the corporate or enterprise level, do not have the same vision
of all decision-making data since their needs vary greatly depending on the application …

Spatial data warehouses store a large amount of historized and aggregated data. They are
usually exploited by Spatial OLAP (SOLAP) systems to extract relevant information …

One of the problems in analyzing large multidimensional databases through OLAP sessions
is that decision makers can be overwhelmed by the size of query answers, while they need a …