You are a member of the data science team at a manufacturing firm, and you are currently examining the company's extensive historical sales dataset, which consists of hundreds of millions of records. During your exploratory data analysis, you have several tasks to perform, including the calculation of descriptive statistics like mean, median, and mode, conducting intricate statistical hypothesis tests, and generating various feature-related plots over time. Your goal is to leverage as much of the sales data as feasible for your analyses while keeping computational resource usage to a minimum. How should you approach this situation?