Databricks Databricks-Certified-Data-Analyst-Associate 시험 개요:
| 인증 벤더: | Databricks |
|---|---|
| 시험명: | Databricks 인증 데이터 분석가 준전문가 시험 |
| 시험 번호: | Databricks-Certified-Data-Analyst-Associate |
| 합격 점수: | 70% |
| 응시료: | $200 USD |
| 시험 형식: | 객관식 |
| 관련 자격증: | Databricks 인증 데이터 엔지니어 준전문가 Databricks 인증 머신 러닝 준전문가 |
| 실제 시험 문항 수: | 45 |
| 시험 시간: | 90분 |
| 자격증 유효 기간: | 2년 |
| 지원 언어: | 영어 |
| 샘플 문제: | Databricks Databricks-Certified-Data-Analyst-Associate 샘플 문제 |
| 응시 방법: | 온라인 감독 시험 또는 시험 센터 감독 시험 |
| 전제 조건: | 정식 선행 조건은 없습니다. Databricks는 데이터 분석과 Databricks SQL에 대한 6개월 이상의 실무 경험을 권장합니다. |
| 공식 요강 URL: | https://www.databricks.com/learn/certification/data-analyst-associate |
Databricks Databricks-Certified-Data-Analyst-Associate 시험요강:
| 주제 | 소개 |
|---|---|
| 주제 1 |
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| 주제 2 |
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| 주제 3 |
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| 주제 4 |
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| 주제 5 |
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참조: https://www.databricks.com/learn/certification/data-analyst-associate
최신 Data Analyst Databricks-Certified-Data-Analyst-Associate 무료샘플문제
문제 #1
Which example of data projects represents a common analytics application to be completed in Databricks SQL?
A. Performing analysis-specific ETL on gold-layer tables
B. Testing the latency of real-time streaming workloads
C. Monitoring the performance of deployed machine learning solutions
D. Predicting customer churn by automatically developing time-series models
문제 #2
What describes the variance of a set of values?
A. Variance is a measure of how far a set of values is spread out from the sets central value.
B. Variance is a measure of how far a single observed value is from a set ot va IN
C. Variance is a measure of how far an observed value is from the variable ' s maximum or minimum value.
D. Variance is a measure of central tendency of a set of values.
문제 #3
A data analyst has a managed table table_name in database database_name. They would now like to remove the table from the database and all of the data files associated with the table. The rest of the tables in the database must continue to exist.
Which of the following commands can the analyst use to complete the task without producing an error?
A. DELETE TABLE database_name.table_name;
B. DROP TABLE table_name FROM database_name;
C. DROP TABLE database_name.table_name;
D. DROP DATABASE database_name;
E. DELETE TABLE table_name FROM database_name;
문제 #4
A data engineering team has created a Structured Streaming pipeline that processes data in micro-batches and populates gold-level tables. The microbatches are triggered every 10 minutes.
A data analyst has created a dashboard based on this gold level data. The project stakeholders want to see the results in the dashboard updated within 10 minutes or less of new data becoming available within the gold- level tables.
What is the ability to ensure the streamed data is included in the dashboard at the standard requested by the project stakeholders?
A. A refresh schedule with an always-on SQL Warehouse (formerly known as SQL Endpoint
B. A refresh schedule with stakeholders included as subscribers
C. A refresh schedule with an interval of 10 minutes or less
D. A refresh schedule with a Structured Streaming cluster
문제 #5
Which of the following approaches can be used to connect Databricks to Fivetran for data ingestion?
A. Use Workflows to establish a cluster for Fivetran to interact with
B. Use Workflows to establish a SQL warehouse (formerly known as a SQL endpoint) for Fivetran to interact with
C. Use Delta Live Tables to establish a cluster for Fivetran to interact with
D. Use Partner Connect ' s automated workflow to establish a cluster for Fivetran to interact with
E. Use Partner Connect ' s automated workflow to establish a SQL warehouse (formerly known as a SQL endpoint) for Fivetran to interact with
질문과 대답:
| 문제 #1 정답: A | 문제 #2 정답: A | 문제 #3 정답: C | 문제 #4 정답: C | 문제 #5 정답: D |














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