Data Source Is Out Of Control

Have you experienced to create an MS Excel reports wherein the source of data is a .CSV file that is extracted from an Oracle system? If yes, then maybe you have also experienced the situation that I have been through.

A few months ago, I closed a contract to develop Purchase Order (PO) performance reports and Sales Order (SO) performance reports with one of my old clients. They looked very simple at first because there was no need for me to create data entry modules for the program. The source of the data would be coming from their Oracle system. Records would be entered from different countries across Asia Pacific and stored them into one central database server. Weekly, they would extract the records from it and convert it to Comma Separated file or .CSV file. My Macro program would import those contents of that .CSV file to my worksheets and somehow needed to consolidate them for reports and analysis purposes.

At first, everything went smoothly. One day, the project liaison called and told me that there have been errors in almost all the reports. She sent me a copy of the macro file and source data file to check on the problems. As I was checking the reports of the Excel file one-by-one, reports were devastated. I investigated for hours all the macro modules but I hadn’t seen any clue of what happened to them. So, I asked myself; “How come a program in a good running condition suddenly gives incorrect figures in almost all reports?” The answer is actually right under my nose. When I checked the records in details, I saw the null values of all the Date Fields like “Actual Shipment Date”, etc. were changed. Originally, if the null date field was converted to .CSV file, the content was “NULL”. It was changed to dash (“-“) and eventually would give incorrect values in reports. To correct the problem, I spent days to modify the program modules and worksheet cell formulas that are related to all the date fields. Whew! It was tedious.

That was a learning experience for me. I didn’t see that coming and hadn’t prepared for it. Partly, it was my fault because I presumed that the records format was final and didn’t realize that the data-entry program and data-conversion program were not mine and it could be changed anytime.

For that particular reason, I requested the project liaison to collaborate with their Oracle programmer to advice us if records structures were altered.

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Number Rounding Off Issue

Three days ago, I was facing a difficult situation. A client of mine was asking me to make percentage-items of a report to sum up exactly to 100%. To visualize what I’m talking about, look at the example of figures below:

# of items ------------->%
7 -------------------------->58.33%
1 -------------------------->8.33%
3 -------------------------->25%
1 -------------------------->8.33%
-----------------------------------------------------------
12 -------------------------->99.99% <------TOTAL

The example above looks incorrect when you add all the percentage items as they are. The percentage total would be 99.99% and not 100%. It is even more incorrect if all percentage items are rounded off to the nearest one. See below:

# of items ------------->%
7 -------------------------->58%
1 -------------------------->8%
3 -------------------------->25%
1 -------------------------->8%
---------------------------------------------------
12 -------------------------->99% <------TOTAL


The total became 99%. But when you put the same calculation to Microsoft Excel, it would display a different result. Please create a New Worksheet in MS Excel and enter the following:

Cell A1 = 7
Cell A2 = 1
Cell A3 = 3
Cell A4 =1
Cell A5 =SUM(A1:A4)

Cell B1 = A1/$A$5

Copy formula of B1 to B3-B4 and copy A5 to B5. Format the entire column B to “Percentage” with zero decimal places. When done, you would see the following result:

# of items ------------->%
7 -------------------------->58%
1 -------------------------->8%
3 -------------------------->25%
1 -------------------------->8%
----------------------------------------------------
12 -------------------------->100% <------TOTAL

The result as you have seen is very interesting. Microsoft treated the value of each individual percentage-item as the number of its formula result and not as what is displayed. This is why the total percentage is 100% and not 99%. In general practices, the MS Excel computation is acceptable to most people and they consider the difference negligible. But there are few people who disagree with this kind of result and consider it unlikely and incorrect to present this type of calculation. Truly, the situation is really a matter of personal point of view and consideration of the person going on this kind of situation.

To satisfy those few people who prefer to have each percentage item to add up to exactly 100%, a VBA script is can be created to do the trick. However, before I present to you the solution, I would like to reiterate that the idea is a matter of preference and most likely debatable to most people because they prefer the Microsoft Excel way. It is correct to some people and the rest of them think otherwise.

Run the script below:



Sub ComputePercentage()

Dim i As Integer
Dim x As Integer
Dim Tot As Single
i = 1
'ROUTINE TO GET THE ROW LOCATION OF THE PERCENTAGE TOTAL
'AFTER THE LOOP i HAS THE ROW NUMBER
Do While Not Cells(i, 2).Formula Like "=SUM*"

i = i + 1

Loop
'COMPUTE THE PERCENTAGES
Tot = 0
For x = 1 To i - 1

If x <> Cells(x, 2) = Round(Cells(x, 1) / Cells(i, 1), 4)

Tot = Tot + Cells(x, 2)

Else

Cells(x, 2) = 1 - Tot

End If

Next x

End Sub

By the way, before you run the program, format the Column B to Percentage with 2 decimal places. When you run the program above, it would give you the following result.

# of items ------------->%
7 -------------------------->58.33%
1 -------------------------->8.33%
3 -------------------------->25.00%
1 -------------------------->8.34%
---------------------------------------------------------
12 -------------------------->100% <------TOTAL

Notice that the last percent number is slightly incorrect. When you divide 1 with 12 the quotient is 8.333333… I will say it again, to those people who prefer it this way, they might consider the inaccuracy of the last number as so small as to be neglected.

It is for you to decide (or your client) which one to use.

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