To understand the role of big data analytics in enhancing strategic and operational decision-making in IT.
To explore how organizations collect, store, process, and analyze large volumes of data for IT-related decisions.
To evaluate tools, platforms, and techniques used in big data analytics across various IT domains.
To identify challenges related to data quality, scalability, and security in big data adoption.
To assess the business impact of data-driven decision-making on IT efficiency, innovation, and performance.
Conduct a literature review on big data concepts, technologies (e.g., Hadoop, Spark), and their relevance in IT decision-making.
Identify and study real-world use cases where big data has influenced key IT decisions (e.g., infrastructure planning, cybersecurity, cloud adoption).
Analyze tools and frameworks used for big data analytics (e.g., Hive, Kafka, Tableau, NoSQL databases).
Explore the integration of analytics with IT dashboards for real-time monitoring and predictive insights.
Collect secondary data or expert inputs (if feasible) on decision outcomes influenced by data analytics.
Identify bottlenecks in implementing big data strategies such as data silos, lack of skills, or integration issues.
Prepare a detailed report with insights, comparative tool analysis, implementation roadmap, and best practices for integrating big data analytics into IT strategy.
