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The data engineering team maintains a Silver table named 'sales_cleaned' with sales data appended in near real-time. They aim to create a Gold-layer entity from 'sales_cleaned' to compute the year-to-date (YTD) sales amount, featuring the schema: country_code STRING, category STRING, ytd_total_sales FLOAT, updated TIMESTAMP. The metrics need daily recalculation but are queried frequently by various business teams, prompting a need to minimize costs and latency. Which solution best fits these requirements?_
A
Define the new entity as a global temporary view for shared computing resources among notebooks or jobs.
B
Set up a nightly batch job to recalculate metrics and overwrite them in a table with each update.
C
Establish multiple tables, one for each business team, to enable quick and efficient metric queries.
D
Define the new entity as a view to prevent persisting results upon each metric recalculation.
E
All the above solutions are suitable, leveraging Databricks' Delta Caching feature.