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In this tutorial, the presenter demonstrates how to efficiently extract fuel data from a large dataset of over 110,000 client rows. Instead of manually copying and pasting, which is time-consuming, a formula is utilized to streamline the process. The presenter starts by creating a new worksheet and applying the "RAND" function to select random values between the first row of the table and 110,000. This generates random numbers to identify specific clients. The tutorial aims to extract a portion of this information efficiently, allowing for mailing or analysis without the hassle of dealing with the entire dataset. The focus is on generating a sample of 20 clients using this method.
