完璧なdbt Labs dbt-Analytics-Engineeringトレーニング資料 & 合格スムーズdbt-Analytics-Engineering資格関連題 | 最高のdbt-Analytics-Engineering試験関連赤本JPTestKingは我々が研究したトレーニング資料を無料に更新します。それはあなたがいつでも最新のdbt-Analytics-Engineering試験トレーニング資料をもらえるということです。dbt-Analytics-Engineering認定試験の目標が変更されば、JPTestKingが提供した勉強資料も変化に追従して内容を変えます。JPTestKing は各受験生のニーズを知っていて、あなたがdbt-Analytics-Engineering認定試験に受かることに有効なヘルプを差し上げます。あなたが首尾よく試験に合格するように、我々は最も有利な価格と最高のクオリティーを提供して差し上げます。 dbt Labs dbt Analytics Engineering Certification Exam 認定 dbt-Analytics-Engineering 試験問題 (Q273-Q278):質問 # 273
You have a time-sensitive incremental model that must run as quickly as possible whenever new data arrives. What dbt feature or configuration might be crucial for optimization?
A. Use the dbt run -select flag to execute only that specific model.
B. Configure the model to run with maximum possible concurrency.
C. Define appropriate materializations (table, view, incremental) for the model.
D. Set the model to refresh on a frequent, time-based schedule.
正解：A、C
解説：
A materially affects how the model is built. C avoids the overhead of running other models. B depends on warehouse concurrency limits. D might be needed, but the choice in A is more fundamental to performance.
質問 # 274
Your fct_orders model depends on both raw_sales and stg_customers. Due to upstream changes, the customer_id column in raw_sales is now named cust_id. How could you manage this change with minimal disruption?
A. Use a dbt source to rename the column in raw sales.
B. Update the fct_orders model to reference cust_id.
C. Create an alias for customer_id as cust_id in the stg_customers model.
D. Utilize dbt's ref() function to dynamically adapt to the new column name.
正解：D
解説：
The ref() function is designed for these situations. It makes your models adaptable to upstream changes. Option A would work but creates maintenance overhead.
質問 # 275
Business requirements call for a report ranking products based on year-over-year (YoY) revenue growth. Historical data must be preserved. What's a potential issue in implementing this directly in a dbt model?
A. Views cannot perform complex date manipulation required for YoY calculations.
B. Incremental materializations aren't suitable for trend analysis.
C. Data warehouses might not be optimized for period-over-period comparisons.
D. ref() functions can hinder performance when working with historical data.
正解：C
解説：
YoY calculations can strain database performance. Consider strategies like pre-aggregating data at the month level. Others issues are less likely to be a bottleneck.
質問 # 276
A CTE within a dbt model is incorrectly casting a string column to a numeric type.
A. A source table has inconsistent data, mixing true numeric values with strings.
B. A Jinja macro meant to filter out non-numeric strings has a logic flaw.
C. A snapshot is incorrectly merging new data with incompatible types into an existing table.
正解：A、B
解説：
This error usually originates from mismatched data types at the database level. CTE logic or source data quality are frequent culprits.
質問 # 277
While working on a pull request, you realize a much better approach exists. Which actions could you take?
A. Add new commits to the existing branch, explaining the change of direction in the comments on the pull request.
B. Make the changes on your branch and use git push -force to overwrite the existing remote branch.
C. Avoid introducing major changes during a pull request, as it hinders effective code review.
D. Close the original pull request, create a new branch, and open a new pull request.
正解：A、D
解説：
B: Provides the cleanest history for the revised approach. C: Maintains transparency on the evolution of your thought process while allowing for review of the new changes.