passmaster16
New Member
- Joined
- Apr 10, 2009
- Messages
- 16
OK, this is a bit of a tricky one.
I am a manager of an internal IT help desk. We're wanting to do some trend analysis on the trouble calls that we receive so that we can perform root cause analysis to eliminate the root problems from our environment. Our trouble tickets do get assigned into general type and subtype categories. This alone helps us identify trends. However I would like to take things a step further and look at the actual call description data to see where we may have trends.
The problem with this approach is that the trouble ticket description for the same issue could vary depending on which analyst opened the call. What I was hoping for was some type of algorithm within Excel or VBA code that could look at a column of data and compare the records to each other to find potential matches. The algorithm would have to look at the data and attempt to match based on keywords. At that point I would like to group those records together or at a minimum flag the matching records with a distinctive color indicating that it is part of a larger group of records. Then at least we have something to go off of to have our people take a closer look at.
I know that Microsoft has a free log parser tool http://www.microsoft.com/downloads/...6b-abf8-4c25-91b2-f8d975cf8c07&displaylang=en but this tool assumes that we have a search string that we're looking for The difficulty with my request is that we may not know the search string. For instance we may receive 5 calls over a month duration of "excel 2007 hangs". We may or may not know how frequent that issue occurred.
Anyway, regarding thie request, I'm not expecting something with 100% accuracy, just somewhat intelligent to compare the records to each other to see if any pattern exists. Then based on the results we could take a closer look to see if the findings are legitimate.
I know this might be difficult or even impossible in Excel but I thought I'd ask.
Any help or suggestions you may be able to offer would be greatly appreciated. Thanks in advance!
I am a manager of an internal IT help desk. We're wanting to do some trend analysis on the trouble calls that we receive so that we can perform root cause analysis to eliminate the root problems from our environment. Our trouble tickets do get assigned into general type and subtype categories. This alone helps us identify trends. However I would like to take things a step further and look at the actual call description data to see where we may have trends.
The problem with this approach is that the trouble ticket description for the same issue could vary depending on which analyst opened the call. What I was hoping for was some type of algorithm within Excel or VBA code that could look at a column of data and compare the records to each other to find potential matches. The algorithm would have to look at the data and attempt to match based on keywords. At that point I would like to group those records together or at a minimum flag the matching records with a distinctive color indicating that it is part of a larger group of records. Then at least we have something to go off of to have our people take a closer look at.
I know that Microsoft has a free log parser tool http://www.microsoft.com/downloads/...6b-abf8-4c25-91b2-f8d975cf8c07&displaylang=en but this tool assumes that we have a search string that we're looking for The difficulty with my request is that we may not know the search string. For instance we may receive 5 calls over a month duration of "excel 2007 hangs". We may or may not know how frequent that issue occurred.
Anyway, regarding thie request, I'm not expecting something with 100% accuracy, just somewhat intelligent to compare the records to each other to see if any pattern exists. Then based on the results we could take a closer look to see if the findings are legitimate.
I know this might be difficult or even impossible in Excel but I thought I'd ask.
Any help or suggestions you may be able to offer would be greatly appreciated. Thanks in advance!
