This is Part 4 of a Case File series that describes how real auditors tried to apply questionable methods to auditing and data profiling. See Part 1, Part 2, Part 3.
Does the Process X team provide metrics around their process?” I asked.
“Yes,” the most senior auditor replied, showing me the web page where the Process X metrics were displayed.
After reviewing the page briefly, I said, “I see they do metrics by month. You have a year’s data; are you planning to understand how they prepare their metrics and re-calculate them to see if you get the same numbers?”
This is Part 3 of a Case File series that describes how real auditors tried to apply questionable methods to auditing and data profiling. See Part 1 and Part 2.
I looked at the third page of the handout and asked, “What is this?”
“A list of Active Directory (AD) groups and the user IDs in each group. I searched AD for any group containing the system name,” the junior auditor said, “and identified these 6 groups. I then downloaded all the members of these groups from AD into Excel.”
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.