Data-Intensive Computing refers to the processing and analysis of large volumes of data, often requiring significant computational resources. This approach is essential in fields like big data analytics, machine learning, and scientific research, where traditional computing methods may struggle to handle the scale and complexity of the data involved. In this context, specialized tools and frameworks, such as Hadoop and Spark, are commonly used to manage and analyze data efficiently. These technologies enable organizations to extract valuable insights from vast datasets, driving informed decision-making and innovation across various industries.