If you’re an auditor and you are not yet using Excel PowerPivot, you are missing the next greatest thing since spreadsheets arrived.
If you are NOT an auditor, and you don’t use PowerPivot, you’re in the same boat with the auditors mentioned above, and it is sinking.
In other words, if you use Excel, you should be learning Excel PowerPivot. It’s that big.
Let me explain why.
NOTE: I updated this post quite a bit with new info…
As I explained in the last Excel post, you can check for blank and invalid data in Excel several ways.
In this post, I will focus on the insights and issues encountered by sorting each column from A to Z and then Z to A.
Sounds pretty simple, but I’m willing to bet you will be surprised to learn a thing or two…
For a list of the reasons why you must validate data before analyzing it, see Why You Must Validate Data.
You can check for blank and invalid data in Excel several ways.
Depending on the size of the file and your preferences, you can either scroll through the dropdown list, sort each column from A to Z and then Z to A, or apply a filter.
Sometimes, you need to use a combination of these methods.
It’s important to know how these methods treat data differently and to be aware of their limitations.
Do you know the #1 reason auditors don’t do data analytics (DA) much?
It is so simple, so obvious, I hesitated to blog about it. Let me know if you agree.
Excel’s Text to Columns function allows you to separate pieces of data in a single column into multiple columns.
This function helps when key data is buried in a field with other information and you need to extract the key data into a separate column before you can analyze it.
For example, you obtain a list of email addresses, and all you want are the user IDs. Or you get a list of servers, and the server name is server.domain.com, and you need just the “server” name. Or you need to separate LastName, First Name into separate columns. That’s where Text to Columns saves the day.
This article is the fourth post in the Excel basic data analytic series.
To identify unique values in an Excel table, follow the steps below.
This article is the third post in the Excel basic data analytic series, which starts here.
The steps for identifying unique values are similar to identifying duplicates. The first difference shows up in step 3 below.
While the previous post in this series described how to remove duplicate values in Excel, this post describes how to identify duplicates.
The remove duplicates function doesn’t tell you which values are duplicates, it just removes them. Sometimes you need a list of the duplicates so you can review them in detail or include them in your workpapers.
So we’ll look at how to create a list of duplicates across all values/columns and in specific columns.