Any way to automate removal of older rows of data?

The challenge described in this post is one that countless spreadsheet users face but rarely articulate as clearly as /u/Skellyhell2 has. The core problem is deceptively simple: keep only the most recent test score for each person across thousands of rows of data. Yet beneath that simplicity lies a task that can consume hours of manual work without the right approach. This is precisely the kind of inefficiency that AI-native spreadsheet tools are designed to eliminate, transforming what feels like a tedious chore into a straightforward, automated process.

What makes this scenario particularly relatable is the combination of scale and nuance. The user isn't dealing with a handful of duplicate entries; they're navigating through 50,000-plus rows where multiple years of test data have accumulated. The "remove duplicates" feature handles easy cases where dates are identical, but it falls short when the same person appears multiple times with different dates. The real challenge emerges when you need a solution that understands "most recent" as a relative concept—one that varies by person. This is where traditional spreadsheet functions often require creative workarounds or complex nested formulas that feel like they're fighting the tool rather than working with it. Similar workflow challenges appear across our community, from Need Excel workflow advice for multi-region data cleanup and tracking progress to discussions about join content from cells in a column without losing content from the corresponding columns, where users are seeking more intuitive ways to manipulate their data.

The underlying reality is that spreadsheet users have become accustomed to piecing together solutions from disparate functions, often relying on trial and error or community forums to discover workarounds. In this case, the user needs a method that groups by person, identifies the maximum date within each group, and then filters to keep only those rows—all while preserving the other columns like first name, last name, and score. Modern spreadsheet tools can absolutely handle this through a combination of sorting, grouping, or formula-based approaches, but the cognitive load of constructing such a solution shouldn't fall entirely on the user. The expectation should be that the tool anticipates these needs and provides accessible pathways to accomplish them.

This post also highlights something important about the evolution of data management expectations. Users like /u/Skellyhell2 are no longer satisfied with simply making do; they're actively seeking optimisation, looking for ways to work smarter rather than longer. The phrase "I imagine excel has some way of pruning older data" reveals both hope and a hint of frustration—hope that a better solution exists, and frustration that finding it requires detective work. This is a microcosm of a broader shift: as data volumes grow across every industry, the gap between what users need to do and what traditional tools make intuitive widens. The future of spreadsheets lies in bridging that gap, making complex data operations feel as simple as the problems they solve.

What should organizations and tool developers take from this? The next generation of spreadsheet technology must move beyond incremental feature additions and instead embrace a fundamental reorientation around user intent. When someone needs to consolidate redundant records, the system should recognize the pattern and offer guidance. When someone is manually processing thousands of rows, the system should proactively suggest automation. The question isn't whether AI-native spreadsheets can solve problems like this one—they can. The question is whether they'll be designed for the users who need them most, at the moment they need them most.