The study focuses on making data processing more efficient in cloud computing by reducing the number of steps needed to join large datasets in MapReduce, which is a common tool for handling big data. Instead of using multiple MapReduce Jobs (MRJs) for these joins, the researchers propose a method that only requires two steps. By breaking down the join process into simpler operations, they achieved good performance results in their experiments. This means that large datasets can be processed faster and with less effort, making data analysis more efficient in cloud computing environments.