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Duplicate data has a way of sitting quietly in a spreadsheet, causing problems nobody notices until something important breaks. A client shows up twice in your CRM export and gets the same email twice. A product SKU is counted double and your inventory totals are off. A name appears twice in a dataset and your PivotTable reports the wrong sum.
The data looked fine. Nobody caught it. And by the time someone did, decisions had already been made from numbers that weren’t right.
Excel has built-in tools to find, highlight, and remove duplicates, and they’re faster and more straightforward than most people expect. Here’s how to use all three.
Before you delete anything, take a look at what you’re dealing with. Highlighting duplicates first gives you a chance to review them in context, which matters — sometimes what looks like a duplicate actually isn’t.
Excel immediately color-codes every duplicate in your selected range. You see exactly what’s there before you touch anything.
For larger datasets where you want more control — or where you need to flag duplicates across a whole row, not just one column — a formula approach gives you a cleaner picture.
In an empty column next to your data, type =COUNTIF(A:A,A2)>1. This checks how many times the value in A2 appears in column A. If it shows up more than once, the formula returns TRUE. Copy it down the column and you’ve got a clear, filterable flag on every row. Sort by that column, and every duplicate rises to the top for review.
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Once you’ve reviewed your data and you’re confident about what needs to go, the actual removal is quick.
Click anywhere inside your data range, go to the Data tab, and click Remove Duplicates. A dialog box asks which columns to check. If a row should only be flagged as a duplicate when every column matches, check all of them. If one column is enough — say, a unique ID or email address — check only that one.
Click OK and Excel removes the duplicate rows instantly, then tells you exactly how many were deleted and how many unique values remain.
If you’re about to build a PivotTable, run a mail merge, or import data into another system, duplicate cleanup isn’t optional — it’s step one. Dirty data going into a clean process still produces bad output. It doesn’t matter how well your formulas are built or how carefully your report is structured; if the underlying data has duplicates, the results aren’t reliable.
Making this check a standard part of your data prep process is one of the highest-return habits a team builds. It takes less than two minutes once you know where to look, and it’s the difference between trusting your reports and quietly wondering about them.
Data management is a core part of CTS Excel Intermediate and Advanced courses.
Contact Custom Training Services to find the right level for your team.
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Common Queries
Most patients recover within a few days, depending on the procedure and aftercare.
Most patients recover within a few days, depending on the procedure and aftercare.
Most patients recover within a few days, depending on the procedure and aftercare.
Most patients recover within a few days, depending on the procedure and aftercare.
Most patients recover within a few days, depending on the procedure and aftercare.
