This is Part 2 of a Case File series that describes how real auditors tried to apply questionable methods to auditing and data profiling. See Part I.
I picked one of the fields and said, “Please show me how you profiled the Status field, for example.”
The auditor proudly projected his Excel spreadsheet on the conference room screen. He said, “I filtered the Status field to display only records containing ‘Complete’, noted the number of filtered records in the lower left corner, and recorded the value and the number of records in the document.”
Some auditors struggle with basic auditing. So when these auditors try to data analysis, well you can imagines how that goes.
I recently met with a team of auditors to give them input on what data profiling would be appropriate to perform. And what analytics might be insightful.
This is Part 1 of a 4-part Case File series that describes how real auditors tried to apply questionable methods to auditing and data profiling. Do not try these methods at home or work. Don’t even dream about them, awake or asleep.
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.