Q: 7
A data organization leader is upset about the data analysis team’s reports being different from the
data engineering team’s reports. The leader believes the siloed nature of their organization’s data
engineering and data analysis architectures is to blame.
Which of the following describes how a data lakehouse could alleviate this issue?
Options
Discussion
Option B. not D. Real-time collab (D) sounds nice but lakehouse architecture is really about both teams using the same data as source of truth. Seen similar question in practice sets.
Option B is correct since a lakehouse lets both teams pull from the same single source of truth. Official Databricks docs mention this as a main benefit for resolving siloed data issues. Seen this approach in practice exams too.
Its D in this case, since real-time collaboration could break silos by letting teams work together directly, not just share data. Think it depends if the question's really asking about technical architecture vs actual process changes though. Open to being convinced otherwise.
B
I don’t think it’s B, C seems more likely since moving both teams under one department could help align their work and reduce silos. Makes sense from a reporting structure angle. Pretty sure but open to better arguments.
C/D? Saw a nearly identical question in a mock, think B is right but D looks tempting here too.
Why not C? Team reports often smooth out when orgs restructure, at least in my experience. The single source of truth thing seems like a trap here.
Frustrating how they try to trick you with the org chart stuff, but I'm picking C.
C not B
Not A, B-had almost this exact question on my exam. Lakehouse means both teams use the same data source so the reports match up. Pretty sure B is what they're looking for.
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