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Exam Databricks-Certified-Professional-Data-Engineer All Questions
Exam Databricks-Certified-Professional-Data-Engineer All Questions

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Databricks Certification Databricks-Certified-Professional-Data-Engineer Question # 36 Topic 4 Discussion

Databricks-Certified-Professional-Data-Engineer Exam Topic 4 Question 36 Discussion:
Question #: 36
Topic #: 4

The business intelligence team has a dashboard configured to track various summary metrics for retail stories. This includes total sales for the previous day alongside totals and averages for a variety of time periods. The fields required to populate this dashboard have the following schema:

Databricks-Certified-Professional-Data-Engineer Question 36

For Demand forecasting, the Lakehouse contains a validated table of all itemized sales updated incrementally in near real-time. This table named products_per_order, includes the following fields:

Databricks-Certified-Professional-Data-Engineer Question 36

Because reporting on long-term sales trends is less volatile, analysts using the new dashboard only require data to be refreshed once daily. Because the dashboard will be queried interactively by many users throughout a normal business day, it should return results quickly and reduce total compute associated with each materialization.

Which solution meets the expectations of the end users while controlling and limiting possible costs?


A.

Use the Delta Cache to persists the products_per_order table in memory to quickly the dashboard with each query.


B.

Populate the dashboard by configuring a nightly batch job to save the required to quickly update the dashboard with each query.


C.

Use Structure Streaming to configure a live dashboard against the products_per_order table within a Databricks notebook.


D.

Define a view against the products_per_order table and define the dashboard against this view.


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