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NEW QUESTION: 1
Note: This question is part of a series of questions that use the same or similar answer choices. An answer choice may be correct for more than one question in the series. Each question is independent of the other questions in this series. Information and details provided in a question apply only to that question.
You are loading data from an OLTP database to a data warehouse.
The OLTP database includes a table (or sales data and a table for refund data.
The data warehouse contains a single table for all the sales and refund data.
Which component should you use to load the data to the data warehouse?
A. the Slowly Changing Dimension transformation
B. the Merge transformation
C. an Execute SQL task
D. the Conditional Split transformation
E. the Data Conversion transformation
F. the Lookup transformation
G. the Aggregate transformation
Answer: B
Explanation:
The Merge transformation combines two sorted datasets into a single dataset. The rows from each dataset are inserted into the output based on values in their key columns.
By including the Merge transformation in a data flow, you can merge data from two data sources, such as tables and files.
References: https://docs.microsoft.com/en-us/sql/integration-services/data- flow/transformations/merge-transformation?view=sql-server-2017

NEW QUESTION: 2
유효하지 않은 데이터, 극단적인 값 또는 데이터 요소 간의 선형 상관 관계를 탐지하도록 설계된 감사 소프트웨어는 어떤 유형의 데이터 분석 도구로 분류 될 수 있습니까?
A. 진단
B. 규범
C. 설명 적
D. 예측 적
Answer: A

NEW QUESTION: 3

A. Option C
B. Option A
C. Option D
D. Option B
Answer: B
Explanation:

NEW QUESTION: 4
확인은 다음에 대한 존재 주장을 해결하는 데 가장 효과적입니다.
A. 위탁 재고 보유.
B. 정기 비즈니스 과정에서의 상품 판매.
C. 조직이 개발 한 특수 프로세스에 대한 특허 부여.
D. 기계 공장에 밀링 머신 추가.
Answer: A