Please someone clarify this question

[Sinduja]

You have a Fabric F32 capacity that contains a workspace. The workspace contains a warehouse named DW1 that
is modelled by using MD5 hash surrogate keys.
DW1 contains a single fact table that has grown from 200 million rows to 500 million rows during the past year.
You have Microsoft Power BI reports that are based on Direct Lake. The reports show year-over-year values.
Users report that the performance of some of the reports has degraded over time and some visuals show errors.
You need to resolve the performance issues. The solution must meet the following requirements:
Provide the best query performance.
Minimize operational costs.
Which should you do?
A.Change the MD5 hash to SHA256.
B.Increase the capacity.
C.Enable V-Order.
D.Modify the surrogate keys to use a different data type.
E.Create views.

[lbendlin · Accepted solution]

None of the above. Run OPTIMIZE to consolidate the files into the desired 1GB chunks, and consider using yearly partitions.

(they want you to increase the capacity, of course)

[Tontaube2]

Ok, Optimize would make sense...but to choose from the available options A-E:

is it:

B) Increase the capacity (only F64 can handle 500 million rows...). But: "Minimize operational costs."

C: Enable V-Order. Well, it's switched on by default - but since WHEN? (I.e., is it a possible "miss" during re-designing the exam?)

[lbendlin]

yes, most likely.  Fabric features are changing at a fast pace, and the exams have a hard time keeping up and staying relevant.

[v-saisrao-msft · Accepted solution]

Hi  @Sinduja,

Thank you for reaching out to Microsoft Fabric Community.

Given the data growth and the performance issues you're seeing in Power BI Direct Lake reports, the best approach would be to enable V-Order. This optimizes columnar storage, improving query performance significantly without increasing costs.

Adding to what @lbendlin said, running OPTIMIZE in your Fabric Warehouse will consolidate small Delta files into efficient 1GB chunks, reducing the overhead on queries. Since your reports rely on year-over-year analysis, implementing yearly partitions can further improve performance by limiting the amount of scanned data.

Scaling up capacity F32 to higher is always an option, but before increasing costs, I would recommend enabling V-Order and optimizing storage. Let us if you any further queries.

If this post helps, then please consider Accepting as solution to help the other members find it more quickly, don't forget to give a "Kudos" – I’d truly appreciate it! 

[lbendlin · Accepted solution]

None of the above. Run OPTIMIZE to consolidate the files into the desired 1GB chunks, and consider using yearly partitions.

(they want you to increase the capacity, of course)