Data Warehouses (DWs), supported by OLAP, have played a key role in helping company decision-making du- ring the last few years. DWs can be stored in ROLAP and/or MOLAP data storage systems. Data is stored in a relational database in ROLAP and in multidimensional matrices in MOLAP. This paper presents a comparative example, analysing the performance and advantages and disadvantages of ROLAP and MOLAP in a specific database management system (DBMS). An overview of DBMS is also given to see how these technologies are being incorporated
In today’s highly specialized business environment, efficient management and product distribution de...
International audienceRecent approaches adopt multimodel databases (MMDBs) to natively handle the va...
Although data warehouses are viewed as organized, summarized repositories of time-oriented data conc...
Data warehousing is the foundation of DSS (decision support system), of which the goal is to enable ...
En los últimos años los Data Warehouses (DW) en conjunto con OLAP se han constituido en elementos de...
OLAP models can be categorized with two types: MOLAP (multidimensional OLAP) and ROLAP (relational O...
ROLAP (Relational OLAP) and MOLAP (Multidimensional OLAP) are two opposing techniques for building O...
With huge amounts of data collected in various kinds of applications, data warehouse is becoming a m...
This thesis deals with the issue of data warehouses and the OLAP. It contains their de nitions and u...
Multi-model DBMSs (MMDBMSs) have been recently introduced to store and seamlessly query heterogeneou...
International audienceMulti-model DBMSs (MMDBMSs) have been recently introduced to store and seamles...
This paper deals with data warehouses and OLAP. These technologies are defined and described here. T...
The large volumes of data that nowadays exist in transactional systems of companies increasingly req...
as the dominant approach in data warehousing with decision support applications. In order to enhance...
There are different types of DatabaseManagement System. Each has their own modeland architecture for...
In today’s highly specialized business environment, efficient management and product distribution de...
International audienceRecent approaches adopt multimodel databases (MMDBs) to natively handle the va...
Although data warehouses are viewed as organized, summarized repositories of time-oriented data conc...
Data warehousing is the foundation of DSS (decision support system), of which the goal is to enable ...
En los últimos años los Data Warehouses (DW) en conjunto con OLAP se han constituido en elementos de...
OLAP models can be categorized with two types: MOLAP (multidimensional OLAP) and ROLAP (relational O...
ROLAP (Relational OLAP) and MOLAP (Multidimensional OLAP) are two opposing techniques for building O...
With huge amounts of data collected in various kinds of applications, data warehouse is becoming a m...
This thesis deals with the issue of data warehouses and the OLAP. It contains their de nitions and u...
Multi-model DBMSs (MMDBMSs) have been recently introduced to store and seamlessly query heterogeneou...
International audienceMulti-model DBMSs (MMDBMSs) have been recently introduced to store and seamles...
This paper deals with data warehouses and OLAP. These technologies are defined and described here. T...
The large volumes of data that nowadays exist in transactional systems of companies increasingly req...
as the dominant approach in data warehousing with decision support applications. In order to enhance...
There are different types of DatabaseManagement System. Each has their own modeland architecture for...
In today’s highly specialized business environment, efficient management and product distribution de...
International audienceRecent approaches adopt multimodel databases (MMDBs) to natively handle the va...
Although data warehouses are viewed as organized, summarized repositories of time-oriented data conc...