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SAP Exam C_DS_43 Topic 5 Question 4 Discussion

Actual exam question for SAP's C_DS_43 exam
Question #: 4
Topic #: 5
[All C_DS_43 Questions]

You built a delta load dataflow to be executed every night. The source table contains a CHANGE

DATE column that is populated by the database when the row is saved.

Which changes can this approach identify in the source based on the CHANGE_DATE column?

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Suggested Answer: C

Contribute your Thoughts:

Melodie
4 months ago
That's a good point. It's important to have a comprehensive approach to identify all types of changes in the source data.
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Marcos
4 months ago
I believe we can use a flag or indicator in the source table to mark rows as deleted, and then filter them out during the delta load process.
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Chauncey
5 months ago
But what about deleted rows? How can we identify those using the CHANGE_DATE column?
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Melodie
5 months ago
Yes, I agree. By comparing the last load date with the CHANGE_DATE column, we can easily determine any changes.
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Marcos
5 months ago
I think this approach can help identify new or updated rows based on the CHANGE_DATE column.
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Christiane
5 months ago
Agreed, it provides a good mechanism for tracking updates and inserts in the source table.
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Agustin
5 months ago
I think this approach is reliable for identifying changes in the source data.
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Sabine
5 months ago
I hope the database admins are keeping that CHANGE_DATE column accurate. If not, this whole setup could fall apart faster than a house of cards in a tornado.
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Olen
4 months ago
We might need to set up some checks to ensure the accuracy of the CHANGE_DATE column to avoid any issues with our dataflow.
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Erinn
4 months ago
I agree, if the database admins are not keeping that column up to date, our delta load dataflow could be unreliable.
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Paul
5 months ago
As long as the CHANGE_DATE column is accurate, we should be able to identify any changes made to the source table.
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Agustin
5 months ago
Those should also be captured, as the CHANGE_DATE will indicate when the row was inserted.
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Elke
5 months ago
The CHANGE_DATE column is a godsend for delta loads. No more guessing or complicated comparisons - just look at that column and you know what's changed.
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Grover
4 months ago
I agree, it simplifies the process of identifying changes for the delta load dataflow.
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Georgeanna
4 months ago
Yes, the CHANGE_DATE column makes it so much easier to track changes in the source table.
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Carri
4 months ago
I agree, it simplifies the process and makes it more efficient.
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Kattie
4 months ago
I agree, no more guessing or complex comparisons needed.
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Erinn
4 months ago
Yes, it makes identifying changes in the source table much easier.
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Shonda
5 months ago
It's so much easier now with the CHANGE_DATE column, no more manual comparisons needed.
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Hannah
5 months ago
It's so convenient to have the CHANGE_DATE column for delta loads.
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Johnson
6 months ago
But what about rows that were inserted after the last delta load?
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Scot
6 months ago
This is a pretty straightforward solution. As long as the CHANGE_DATE column is reliable, I don't see any issues with this approach.
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Antonette
6 months ago
Clever idea to use the CHANGE_DATE column. It will make it easy to see exactly when each row was modified, which is crucial for a delta load.
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Charlesetta
4 months ago
Delta loads are efficient for processing incremental changes in data.
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Ruth
4 months ago
Using the CHANGE_DATE column is a smart way to implement delta loads.
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Micaela
5 months ago
Make sure the delta load process captures all necessary changes.
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Helene
5 months ago
The CHANGE_DATE column is key for tracking changes in the source table.
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Jerry
5 months ago
It can't identify rows that have been deleted from the source.
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Floyd
5 months ago
It can identify rows that have been updated since the last load.
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Marcos
6 months ago
It can identify new rows added since the last load.
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Beatriz
6 months ago
This approach can identify all changes made to the source table, regardless of when they occurred. The CHANGE_DATE column is the key to tracking the updates.
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Christiane
6 months ago
Yes, I agree. The CHANGE_DATE column will capture the timestamp of when the row was last modified.
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Agustin
6 months ago
I think this approach can identify all rows that have been updated since the last delta load.
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