OLAP

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Design of complex Data Warehouse: E-Pivot Table

Collaborative design of Data Warehouse

ProtOLAP: OLAP prototyping

The approaches to data warehouse design are based on the assumption that source data are known in advance and available. While this assumption is true in common project situations, in some peculiar contexts it is not. This is the case of the French national project for analysis of energetic agricultural farms, that is the case study of this paper. Here, the above-mentioned methods can hardly be applied because source data can only be identified and collected once user requirements indicate a need. Besides, the users involved in this project found it very hard to express their analysis needs in abstract terms, i.e., without visualizing sample

results of queries, which in turn would require availability of source data. To solve this deadlock we propose ProtOLAP, a tool- assisted fast prototyping methodology that enables quick and reliable test and validation of data warehouse schemata in situations where data supply is collected on users’ demand and users’ ICT skills are minimal. To this end, users manually feed sample realistic data into a prototype created by designers, then they access and explore these sample data using pivot tables to validate the prototype.

SimOLAP: OLAP for simulation data

Data Warehouses and OLAP systems allow decision-makers exploring and analyzing huge volumes of data modeled according the multidimensional model, and extracted from heterogeneous data sources. Usually, DW design is a complex, and time and resources consuming task. Then, DW experts are necessary during design and implementation phases. In this paper, we present a new methodology and a tool allowing modelers (DW unskilled users) to design and implement DWs for analyzing simulation results data by themselves, without any intervention of DW experts.

WikiOLAP

Nowadays, organizations deploy DW and OLAP systems allowing decision-makers to analyze huge volume of data by the simple interaction with user-friendly graphical displays and pivot tables. However, these systems do not present any functionality allowing for collaborative multidimensional

on-line analysis, which is mandatory when the number of decision-makers is important and they are physically located on different sites. At the same time, the information usage of organizations moves towards using more and more Web 2.0 technologies (such as wikis, blogs, etc.) that allow collaborative work and represent a new effective discovery knowledge method. Motivated by the need to improve, we propose an OLAP systems with collaborative work tools, the WikiOLAP system. WikiOLAP integrates advanced OLAP and wiki functionalities in a user-friendly, interactive and effective Service Oriented Architecture. Contrary to existing previously collaborative tools that associate wiki pages to static elements of the OLTP systems, WikiOLAP extends these by associating an ad-hoc wiki olap page to each interesting query.