nerdexam
DatabricksDatabricks

CERTIFIED-DATA-ENGINEER-PROFESSIONAL · Question #60

CERTIFIED-DATA-ENGINEER-PROFESSIONAL Question #60: Real Exam Question with Answer & Explanation

The correct answer is A: Implement the appropriate aggregate logic as a batch read against the daily_store_sales table. See the full explanation below for the reasoning.

Designing and Implementing Data Ingestion and Transformation Pipelines

Question

The data engineering team maintains a table of aggregate statistics through batch nightly updates. This includes total sales for the previous day alongside totals and averages for a variety of time periods including the 7 previous days, year-to-date, and quarter-to-date. This table is named store_saies_summary and the schema is as follows: The table daily_store_sales contains all the information needed to update store_sales_summary. The schema for this table is: store_id INT, sales_date DATE, total_sales FLOAT If daily_store_sales is implemented as a Type 1 table and the total_sales column might be adjusted after manual data auditing, which approach is the safest to generate accurate reports in the store_sales_summary table?

Options

  • AImplement the appropriate aggregate logic as a batch read against the daily_store_sales table
  • BImplement the appropriate aggregate logic as a batch read against the daily_store_sales table
  • CImplement the appropriate aggregate logic as a batch read against the daily_store_sales table
  • DImplement the appropriate aggregate logic as a Structured Streaming read against the
  • EUse Structured Streaming to subscribe to the change data feed for daily_store_sales and apply

Topics

#Batch Processing#Data Accuracy#Data Pipeline Design#SCD Type 1

Community Discussion

No community discussion yet for this question.

Full CERTIFIED-DATA-ENGINEER-PROFESSIONAL PracticeBrowse All CERTIFIED-DATA-ENGINEER-PROFESSIONAL Questions