How does a pivot table change the handling of large datasets?

A pivot table is a powerful tool that significantly enhances the handling of large datasets by transforming complex data into more manageable summaries. This capability allows users to aggregate, analyze, and present data in a concise format. By summarizing data through various dimensions such as categories, dates, or numerical values, users can quickly identify trends, patterns, and insights without getting bogged down by the sheer volume of information.

For example, in a large dataset containing sales records, a pivot table can help summarize total sales by region, product, or time period, allowing users to focus on the most relevant aspects of the data. This streamlined format makes it easier for analysts to draw conclusions and make data-driven decisions.

In contrast, the other options do not accurately reflect the role of pivot tables. Eliminating the need for technology misrepresents the way pivot tables operate, as they are themselves a technological tool. Complicating the analysis process is the opposite of what pivot tables are designed to do—they simplify it. Lastly, limiting data access to certain users does not relate to the primary function of pivot tables, which is to enhance data analysis rather than restrict user permissions.