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A framework for dynamic metrics tracking and data visualization/ Borja, Samuel.--

By: Material type: TextTextPublication details: Manila: Technological University of the Philippines, 2025.Description: x, 131pages: 29cmContent type:
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  • BTH T 58.5 B67 2025
Dissertation note: College of Science.-- Bachelor of science in information technology: Technological University of the Philippines, 2025. Summary: The integration of technology in modern businesses and organizations has become significant, and having a reliable way to track metrics and access insights in real-time is fundamental for making informed, apt, and data-driven business decisions. As a response to these advancements, the study entitled, “A Framework for Dynamic Metrics Tracking and Data Visualization” explores the development of a structured framework for dynamic metrics tracking and data visualization using a powerful out-of-the-box tool from Microsoft Power BI which provides functionalities for data integration, transformation, and presentation. The system consolidates data from multiple enterprise platforms such as SharePoint, Jira, OpsGenie, and SQL databases into unified, interactive dashboards customized based on business needs. These dashboards created in a unified platform provide actionable insights into key performance indicators (KPIs), and this enables decision-makers, executives, and even non-technical users to identify inefficiencies, monitor trends, and make timely interventions that support the annotations team and continuous improvement team. Python and Power BI are the essential tools used to develop this framework following a structured methodology for implementing visualization strategies, building data models, and improving reporting processes. A survey instrument based on ISO 25010, an evaluation instrument based on Functional Suitability and Reliability to identify the level of adequacy of the system was used to assess the final output. The results from the live working environment highlighted that the system met expectations in terms of ease of access, data accuracy, and visualization quality. The framework was rated with an overall mean of 4.8 described as “HIGHLY ACCEPTABLE” by the stakeholders who regularly interact with the metrics, indicating its usefulness in enhancing transparency, organizational responsiveness, and performance monitoring. This study provides a model and guide for organizations that want to utilize and maximize business intelligence tools for data governance and operational administration.
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Item type Current library Shelving location Call number Copy number Status Date due Barcode
Bachelor's Thesis COS Bachelor's Thesis COS TUP Manila Library Thesis Section-2nd floor BTH T 58.5 B67 2025 (Browse shelf(Opens below)) c.1 Not for loan BTH0006644

Bachelor's thesis


College of Science.--
Bachelor of science in information technology: Technological University of the Philippines,
2025.

Includes bibliographic references and index.

The integration of technology in modern businesses and organizations has become
significant, and having a reliable way to track metrics and access insights in real-time is
fundamental for making informed, apt, and data-driven business decisions. As a response
to these advancements, the study entitled, “A Framework for Dynamic Metrics Tracking
and Data Visualization” explores the development of a structured framework for dynamic
metrics tracking and data visualization using a powerful out-of-the-box tool from Microsoft
Power BI which provides functionalities for data integration, transformation, and
presentation. The system consolidates data from multiple enterprise platforms such as
SharePoint, Jira, OpsGenie, and SQL databases into unified, interactive dashboards
customized based on business needs. These dashboards created in a unified platform
provide actionable insights into key performance indicators (KPIs), and this enables
decision-makers, executives, and even non-technical users to identify inefficiencies,
monitor trends, and make timely interventions that support the annotations team and
continuous improvement team. Python and Power BI are the essential tools used to develop
this framework following a structured methodology for implementing visualization
strategies, building data models, and improving reporting processes. A survey instrument
based on ISO 25010, an evaluation instrument based on Functional Suitability and
Reliability to identify the level of adequacy of the system was used to assess the final
output. The results from the live working environment highlighted that the system met
expectations in terms of ease of access, data accuracy, and visualization quality. The
framework was rated with an overall mean of 4.8 described as “HIGHLY ACCEPTABLE”
by the stakeholders who regularly interact with the metrics, indicating its usefulness in
enhancing transparency, organizational responsiveness, and performance monitoring. This
study provides a model and guide for organizations that want to utilize and maximize
business intelligence tools for data governance and operational administration.

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