Data warehouses and Online Analysis Processing (OLAP) have acknowledged and efficient solutions for helping in the decisionmaking process. Through OLAP operators, online analysis enables the decision-maker to navigate and view data represented in a multi-dimensional manner. But when the data or objects to be analyzed are complex, it is necessary to redefine and enhance the abilities of the OLAP...

OLAP queries involve a lot of aggregations on a large amount of data in data warehouses. To process expensive OLAP queries efficiently, we propose a new method for rewriting a given OLAP query using various kinds of materialized aggregate views which already exist in data warehouses. We first define the normal forms of OLAP queries and materialized views based on the lattice of dimension hierar...

Exploiting Resource Description Framework (RDF) data for Online Analytical Processing (OLAP), especially Linked Open Data (LOD), could allow analysts to obtain interesting insights. To conduct OLAP analysis over RDF data, analysts should know the specific semantics, structure, and querying mechanisms of such data. Furthermore, these data should ideally adhere to a multidimensional structure to ...

With the rapid growth in mobile and wireless technologies and the availability, pervasiveness and cost effectiveness of wireless networks, mobile computers are quickly becoming the normal front-end devices for accessing enterprise data. In this paper, we are addressing the issue of efficient delivery of business decision support data in the form of summary tables to mobile clients − mobile OLAP...

We propose an index structure, called measure attribute (MA) index, and a query processing technique to improve OLAP query performance. OLAP queries are extremely complicated due to representing the intricate business logic of the company on a huge quantity of data. This is why the efficient query evaluation becomes a critical issue in OLAP systems. Proposed query processing technique supports ...

On-Line Analytical Processing (OLAP) is a data analysis approach to support decision-making. On top of that, Exploratory OLAP is a novel initiative for the convergence of OLAP and the Semantic Web (SW) that enables the use of OLAP techniques on SW data. Moreover, OLAP approaches exploit different metadata artifacts (e.g., queries) to assist users with the analysis. However, modeling and sharing...

In light of the increasing requirement for processing multidimensional queries on OLAP (relational) data, the database community has focused on the queries (especially range queries) on the large OLAP datasets from the view of multidimensional data. It is well-known that multidimensional indices are helpful to improve the performance of such queries. However, we found that much information irre...

On-line analytical processing (OLAP) systems deal with analytical tasks in businesses. As these tasks do not depend on the latest updates by transactions, it is assumed that the data used in OLAP systems are kept in a data warehouse, which separates the input from operational databases from the outputs to OLAP. Typical OLAP queries are data intensive, and thus time consuming. In order to speed ...

Commercial OLAP systems usually treat OLAP dimensions as static entities. In practice, dimension updates are often needed to adapt the warehouse to changing requirements. In earlier work, we defined a taxonomy for these dimension updates and a minimal set of operators to perform them. In this paper we present TSOLAP, an OLAP server supporting fully dynamic dimensions. TSOLAP conforms to the OLE...

We propose a framework for efficient OLAP on information networks with a focus on the most interesting kind, the topological OLAP (called “TOLAP”), which incurs topological changes in the underlying networks. T-OLAP operations generate new networks from the original ones by rolling up a subset of nodes chosen by certain constraint criteria. The key challenge is to efficiently compute measures f...