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Databricks Exam Databricks Certified Data Engineer Professional Topic 6 Question 38 Discussion

Actual exam question for Databricks's Databricks Certified Data Engineer Professional exam
Question #: 38
Topic #: 6
[All Databricks Certified Data Engineer Professional Questions]

To reduce storage and compute costs, the data engineering team has been tasked with curating a series of aggregate tables leveraged by business intelligence dashboards, customer-facing applications, production machine learning models, and ad hoc analytical queries.

The data engineering team has been made aware of new requirements from a customer-facing application, which is the only downstream workload they manage entirely. As a result, an aggregate table used by numerous teams across the organization will need to have a number of fields renamed, and additional fields will also be added.

Which of the solutions addresses the situation while minimally interrupting other teams in the organization without increasing the number of tables that need to be managed?

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Suggested Answer: B

This is the correct answer because it addresses the situation while minimally interrupting other teams in the organization without increasing the number of tables that need to be managed. The situation is that an aggregate table used by numerous teams across the organization will need to have a number of fields renamed, and additional fields will also be added, due to new requirements from a customer-facing application. By configuring a new table with all the requisite fields and new names and using this as the source for the customer-facing application, the data engineering team can meet the new requirements without affecting other teams that rely on the existing table schema and name. By creating a view that maintains the original data schema and table name by aliasing select fields from the new table, the data engineering team can also avoid duplicating data or creating additional tables that need to be managed. Verified Reference: [Databricks Certified Data Engineer Professional], under ''Lakehouse'' section; Databricks Documentation, under ''CREATE VIEW'' section.


Contribute your Thoughts:

Izetta
2 days ago
I'm not entirely sure, but I think creating a new table and using Delta Lake's deep clone functionality could be risky. It might complicate things more than necessary.
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Arletta
8 days ago
I remember we discussed the importance of minimizing disruption to other teams. Option B seems like it could be a good choice since it creates a view to maintain the original schema.
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Stephanie
13 days ago
A is an interesting idea, but I'm not sure how practical it would be to have all the users revert their queries. Seems like a lot of extra work for the other teams. I'd want to explore the other options first.
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Youlanda
19 days ago
E seems the riskiest to me. Overwriting the table in place without giving other teams enough time to adjust could cause a lot of disruption. I'd want to avoid that if possible.
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Lenora
24 days ago
I'm leaning towards C with the Delta Lake deep clone functionality. That way we can sync the changes to the new table without having to worry about other teams' queries breaking. But I'd need to research that approach a bit more to be confident.
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Octavio
29 days ago
Option D seems like the cleanest solution to me. Replacing the current table with a view and creating a new table for the customer-facing app keeps things simple and avoids having to manage multiple versions of the same data.
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Blondell
1 month ago
This is a tricky one. I'm not sure if I fully understand all the implications of the different options, but I think B might be the best approach to minimize disruption to other teams.
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Cecily
2 months ago
Option B seems like the best solution here. Creating a new table with the required fields and maintaining the original schema through a view is a clean way to handle the change without disrupting other teams.
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Dewitt
2 months ago
I disagree, I believe option D is more efficient.
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Hubert
2 months ago
I think option B is the best solution.
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