70-463 · Question #114
You are running a training exercise for Microsoft SQL Server 2012 junior administrators. You are discussing data quality projects. Which of the following are benefits of data quality projects?…
The correct answer is A. It enables you to perform data cleansing on your source data by using the knowledge in a C. It allows you to perform data matching on your source data by using the matching policy in a. DQS data quality projects provide two core benefits: data cleansing using knowledge base domain knowledge, and data matching using the matching policy defined within a DQS knowledge base.
Question
You are running a training exercise for Microsoft SQL Server 2012 junior administrators. You are discussing data quality projects. Which of the following are benefits of data quality projects? (Choose all that apply.)
Options
- AIt enables you to perform data cleansing on your source data by using the knowledge in a
- BIt allows you to perform data matching on your source data by using the knowledge in a DQS
- CIt allows you to perform data matching on your source data by using the matching policy in a
- DIt enables you to perform data cleansing on your source data by using the matching policy in
How the community answered
(27 responses)- A89% (24)
- B4% (1)
- D7% (2)
Why each option
DQS data quality projects provide two core benefits: data cleansing using knowledge base domain knowledge, and data matching using the matching policy defined within a DQS knowledge base.
DQS projects enable data cleansing by applying the cleansing knowledge stored in a DQS knowledge base - including domain rules and reference data - to correct and standardize source data values.
Data matching is performed using the matching policy specifically, not general 'knowledge in a DQS knowledge base'; the matching policy is a distinct component from the cleansing knowledge used in domain management.
Data matching in DQS projects is governed by the matching policy component of a DQS knowledge base, which defines matching rules and weights used to identify duplicate or similar records in source data.
Data cleansing uses domain rules and cleansing knowledge defined in the knowledge base, not the matching policy, which is a separate component designed exclusively for deduplication.
Concept tested: DQS data quality project cleansing and matching policy benefits
Source: https://learn.microsoft.com/en-us/sql/data-quality-services/data-quality-projects-dqs
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