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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
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Showing 1 to 4 of 4 (0.088 seconds)| 1 |
In-memory Business Intelligence : Verifying its Benefits against Conventional ApproachesSakulsorn, Pattaravadee January 2013 (has links)
Business intelligence project failures in organizations derive from various causes. Technological aspects regarding the use of business intelligence tools expose the problem of too complicated tool for operational users, lack of system scalability, dissatisfied software performance, and hard coded business requirements on the tools. This study was conducted in order to validate in-memory business intelligence advantages towards functionality, flexibility, performance, ease of use, and ease of development criteria. A case study research method had been applied to achieve the goals in this thesis. Primarily, a pilot study was carried out to collect the data both from literatures and interviews. Therefore, the design of test case had been developed. Types of testing can be divided into 2 categories: BI functionality test and performance test. The test results reveal that in-memory business intelligence enhances conventional business intelligence performance by improving the software’s loading time and response time. At the meantime, it was proved to be flexible than rule-based, query-based, and OLAP tools, whereas its functionality and ease of development were justified to be better than query-based system. Moreover, in-memory business intelligence provides a better ease of use over query-based and rule-based business intelligence tools. Pair wise comparisons and analyses between selected in-memory business intelligence tool, QlikView, and conventional business intelligence software, Cognos, SAS, and STB Reporter, from 3 banks were made in this study based on the aforementioned test results.
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Combining Business Intelligence, Indicators, and the User Requirements Notation for Performance MonitoringJohari Shirazi, Iman 26 November 2012 (has links)
Organizations use Business Intelligence (BI) systems to monitor how well they are meeting
their goals and objectives. Yet, very often BI systems do not include clear models of
the organization’s goals or of how to measure whether they are satisfied or not. Several
researchers now attempt to integrate goal models into BI systems, but there are still major
challenges related to how to get access to the BI data to populate the part of the goal
model (often indicators) used to assess goal satisfaction.
This thesis explores a new approach to integrate BI systems with goal models. In
particular, it explores the integration of IBM Cognos Business Intelligence, a leading BI
tool, with an Eclipse-based goal modeling tool named jUCMNav. jUCMNav is an open
source graphical editor for the User Requirements Notation (URN), which includes the
Use Case Map notation for scenarios and processes and the Goal-oriented Requirement
Language for business objectives. URN was recently extended with the concept of Key
Performance Indicator (KPI) to enable performance assessment and monitoring of business
processes. In jUCMNav, KPIs are currently calculated or modified manually. The
new integration proposed in this thesis maps these KPIs to report elements that are generated
automatically by Cognos based on the model defined in jUCMNav at runtime, with
minimum effort. We are using IBM Cognos Mashup Service, which includes web services
that enable the retrieval of report elements at the most granular level. This transformation
provides managers and analysts with useful goal-oriented and process-oriented
monitoring views fed by just-in-time BI information. This new solution also automates
retrieving data from Cognos servers, which helps reducing the high costs usually caused
by the amount of manual work required otherwise.
The novel approach presented in this thesis avoids manual report generation and
minimizes any contract with respect to the location of manually created reports, hence
leading to better usability and performance. The approach and its tool support are illustrated
with an ongoing example, validated with a case study, and verified through testing.
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| 3 |
Combining Business Intelligence, Indicators, and the User Requirements Notation for Performance MonitoringJohari Shirazi, Iman 26 November 2012 (has links)
Organizations use Business Intelligence (BI) systems to monitor how well they are meeting
their goals and objectives. Yet, very often BI systems do not include clear models of
the organization’s goals or of how to measure whether they are satisfied or not. Several
researchers now attempt to integrate goal models into BI systems, but there are still major
challenges related to how to get access to the BI data to populate the part of the goal
model (often indicators) used to assess goal satisfaction.
This thesis explores a new approach to integrate BI systems with goal models. In
particular, it explores the integration of IBM Cognos Business Intelligence, a leading BI
tool, with an Eclipse-based goal modeling tool named jUCMNav. jUCMNav is an open
source graphical editor for the User Requirements Notation (URN), which includes the
Use Case Map notation for scenarios and processes and the Goal-oriented Requirement
Language for business objectives. URN was recently extended with the concept of Key
Performance Indicator (KPI) to enable performance assessment and monitoring of business
processes. In jUCMNav, KPIs are currently calculated or modified manually. The
new integration proposed in this thesis maps these KPIs to report elements that are generated
automatically by Cognos based on the model defined in jUCMNav at runtime, with
minimum effort. We are using IBM Cognos Mashup Service, which includes web services
that enable the retrieval of report elements at the most granular level. This transformation
provides managers and analysts with useful goal-oriented and process-oriented
monitoring views fed by just-in-time BI information. This new solution also automates
retrieving data from Cognos servers, which helps reducing the high costs usually caused
by the amount of manual work required otherwise.
The novel approach presented in this thesis avoids manual report generation and
minimizes any contract with respect to the location of manually created reports, hence
leading to better usability and performance. The approach and its tool support are illustrated
with an ongoing example, validated with a case study, and verified through testing.
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| 4 |
Combining Business Intelligence, Indicators, and the User Requirements Notation for Performance MonitoringJohari Shirazi, Iman January 2012 (has links)
Organizations use Business Intelligence (BI) systems to monitor how well they are meeting
their goals and objectives. Yet, very often BI systems do not include clear models of
the organization’s goals or of how to measure whether they are satisfied or not. Several
researchers now attempt to integrate goal models into BI systems, but there are still major
challenges related to how to get access to the BI data to populate the part of the goal
model (often indicators) used to assess goal satisfaction.
This thesis explores a new approach to integrate BI systems with goal models. In
particular, it explores the integration of IBM Cognos Business Intelligence, a leading BI
tool, with an Eclipse-based goal modeling tool named jUCMNav. jUCMNav is an open
source graphical editor for the User Requirements Notation (URN), which includes the
Use Case Map notation for scenarios and processes and the Goal-oriented Requirement
Language for business objectives. URN was recently extended with the concept of Key
Performance Indicator (KPI) to enable performance assessment and monitoring of business
processes. In jUCMNav, KPIs are currently calculated or modified manually. The
new integration proposed in this thesis maps these KPIs to report elements that are generated
automatically by Cognos based on the model defined in jUCMNav at runtime, with
minimum effort. We are using IBM Cognos Mashup Service, which includes web services
that enable the retrieval of report elements at the most granular level. This transformation
provides managers and analysts with useful goal-oriented and process-oriented
monitoring views fed by just-in-time BI information. This new solution also automates
retrieving data from Cognos servers, which helps reducing the high costs usually caused
by the amount of manual work required otherwise.
The novel approach presented in this thesis avoids manual report generation and
minimizes any contract with respect to the location of manually created reports, hence
leading to better usability and performance. The approach and its tool support are illustrated
with an ongoing example, validated with a case study, and verified through testing.
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