Facilitate Effective Decision-Making by Warehousing Reduced Data

Abstract

The authors' aim is to provide a solution for multidimensional data warehouse's reduction based on analysts' needs which will specify aggregated schema applicable over a period of time as well as retain only useful data for decision support. Firstly, they describe a conceptual modeling for multidimensional data warehouse. A multidimensional data warehouse's schema is composed of a set of states. Each state is defined as a star schema composed of one fact and its related dimensions. The derivation between states is carried out through combination of reduction operators. Secondly, they present a meta-model which allows managing different states of multidimensional data warehouse. The definition of reduced and unreduced multidimensional data warehouse schema can be carried out by instantiating the meta-model. Finally, they describe their experimental assessments and discuss their results. Evaluating their solution implies executing different queries in various contexts: unreduced single fact table, unreduced relational star schema, reduced star schema and reduced snowflake schema. The authors show that queries are more efficiently calculated within a reduced star schema.

A linear programming-based framework for handling missing data in multi-granular data warehouses

“…They propose a conceptual model and its implementation in a relational DBMS. (Atigui et al, 2015) study the reduction of data warehouse proposing a constellation schema, where detailed measures of a DW are aggregated and stored into another DW. (Iftikhar & Pedersen, 2010) propose different logical models, extending the classical multidimensional schemata for measures at different temporal granularities.…”

Managing Reduction in Multidimensional Databases

“…The above-mentioned work only allows reducing a fact. Our previous work [1] generalizes the reduction to a complete MDW. Consequently, both facts and dimensions can be reduced.…”

“…Based on this conceptual reduced MDB modeling, our previous work [1] presents some multidimensional analyses operators allowing (i) choosing analysis subjects and axes (i.e. Display), (ii) aggregating data (i.e.…”

“…Our aim is to support effective and efficient decision-making by storing only data of high informative value over time in a MDB. In our previous work [1], we proposed a conceptual modeling solution for MDBs with data reduction (i.e. reduced MDBs).…”

OLAP Analysis Operators for Multi-State Data Warehouses

“…To evaluate the efficiency of multi-state OLAP analyses, we can study query execution efficiency in reduced and unreduced MDWs. In our previous work (Atigui, Ravat, Song, Teste, & Zurfluh, 2015;Atigui, Ravat, Song, & Zurfluh, 2014), we have compared some key indicators about query execution efficiency by applying different types of queries to different types of R-OLAP MDWs. Several experimental assessments are carried out in DBMS Oracle 11g with the following hardware configuration:…”