Webclass 39: A review of the top 40 errors committed by data analysts

Q1. What should we always start with when doing data analytics? (single choice)

Verifiable totals

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Detailed tests

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Q2. Where do we get the most errors if we are analyzing data from a SAP ERP system? (single choice)

Lack of SAP knowledge

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Extraction errors

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Coding errors

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Errors due to a lack of business knowledge

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Errors due to Excel files in different language regions

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Q3. What is document flow? (single choice)

For example, the purchase order, the goods receipt(s) for the purchase order, the invoice(s) for the goods receipt(s) and the payment(s) for the invoice(s)

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The interface between the CRM and the SAP system

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The internal control approbation flow for the purchase order

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Q4. What do we mean by “walking backwards”? (single choice)

First we reconcile the trial balance to the general ledger, then the general ledger to the auxiliary journals, then the auxiliary journals to the operational data.

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Carrying out a walkthrough to verify the internal controls that are acting on a business process.

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Q5. What would be the result of a tab character in a text field for a text file extracted as a tab-delimited file? (single choice)

The columns in your data set would be pushed to the right in the data tool that you are using, once the data has been imported and you will get incorrect data in some columns and for the rows that had the tab character in the text field.

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It will be impossible to import your file into your data analytics tool and you will get a warning error message.

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Q6. Why might you only have a subset of data? (single choice)

The person extracting the data filtered on a posting key, document type, business area, etc.

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Because your staff accidentally duplicated the source files.

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Q7. Why is it important to think about whether or not the field that you are using to link tables together has duplicated values? (single choice)

Because duplicated values on a key field can cause the result of your joined tables to be missing records or to repeat data (such as values) and this could lead you to incorrect audit conclusions.

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Because your data might not be sorted correctly.

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Q8. Why is it important to think about whether or not your data is “at date” or “movements over a period”? (single choice)

Because, for example, you might incorrectly use the value in stock to mean the value of stock today, rather than at the date of the extraction. Or you might incorrectly consider the value of a stock movement to be the total value in stock at the date of the stock movement, rather than just the value of stock moving.

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Because "at date" data shows you the value of transactions over time.

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Q9. Why might your auditor incorrectly conclude that there was a supplier payment to a bank account that had not been entered into the supplier master data? (single choice)

Because the supplier payment may have occurred in a prior period before the supplier bank account was changed and the supplier master data may only show the latest version for the bank account.

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Actually the auditor would be correct in their conclusions.

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Q10. Why would a dashboard that adds up all local currency amounts for all companies in your data set be potentially misleading? (single choice)

Because the different companies' codes might have different house currencies and it would be incorrect to do the total of USD and CNY together.

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Because all dashboards should only be done on one company data-set at a time

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Webclass 39: A review of the top 40 errors committed by data analysts

Webclass 39: A review of the top 40 errors committed by data analysts

admin June 9, 2026

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