This research study aims to investigate the impact, challenges, and benefits of data-driven decision-making in IT technology from an organizational perspective.In today's rapidly evolving technological landscape, organizations increasingly rely on data-driven decision-making to drive their IT technology management strategies. By exploring the intersection of data analytics, IT management, and decision-making processes, this research aims to provide insights into how organizations can leverage data-driven approaches to optimize IT operations and enhance overall IT performance.This research aims to bridge the gap between data analytics and IT technology management by providing evidence-based insights and practical recommendations for organizations to enhance their decision-making processes in the context of IT technology. By embracing data-driven approaches, organizations can leverage the power of data to make informed, timely, and strategic decisions, ultimately driving innovation, improving operational efficiency, and gaining a competitive edge in the digital era.The study will make use of a mixed-methods research approach, combining qualitative and quantitative techniques to collect and analyze data. Through in-depth interviews with IT managers and data analytics professionals, the qualitative phase will explore the organizational factors that influence data-driven decision-making, including organizational culture, leadership support, and the role of data analytics teams. Case studies will also be conducted to examine successful implementations of data-driven decision-making in IT technology management.The quantitative phase of the research will involve the collection and analysis of quantitative data from organizations practicing data-driven decision-making in their IT technology management. Data will be gathered on key performance indicators such as operational efficiency, cost optimization, and customer satisfaction to assess the impact and effectiveness of data-driven decision-making initiatives. Statistical techniques, including regression analysis and correlation analysis, will be employed to identify relationships between data-driven decision-making practices and organizational outcomes.The findings of this research will contribute significantly to the body of knowledge on data-driven decision-making in IT technology management. By identifying best practices, challenges, and opportunities, organizations will gain valuable insights into how to leverage data analytics, ensure data quality, and address ethical considerations for effective decision-making.The research outcomes will serve as a guide for organizations seeking to adopt and implement data-driven decision-making practices, enabling them to improve IT performance, optimize resource allocation, and align IT strategies with organizational goals
