SQL Server Data Quality Services databases
E937633
SQL Server Data Quality Services databases are a set of specialized SQL Server databases that store knowledge bases, data quality rules, and operational data used to profile, cleanse, and match data within the Data Quality Services framework.
All labels observed (1)
| Label | Occurrences |
|---|---|
| SQL Server Data Quality Services databases canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T11655646 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
Target entity: SQL Server Data Quality Services databases Context triple: [DQS_MAIN, partOf, SQL Server Data Quality Services databases]
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A.
SSIS Catalog
SSIS Catalog is a centralized SQL Server repository and management framework for deploying, storing, configuring, and monitoring SQL Server Integration Services (SSIS) projects and packages.
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B.
SQL Server Management Data Warehouse
SQL Server Management Data Warehouse is a SQL Server feature that collects, stores, and reports performance and configuration data from managed servers to support monitoring and analysis.
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C.
SQL Server Integration Services
SQL Server Integration Services is a Microsoft ETL and data integration platform used to extract, transform, and load data between diverse sources within the SQL Server ecosystem.
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D.
MSIServer
MSIServer is the Windows service that manages installation, modification, and removal of software using the Windows Installer technology.
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E.
SQL Server
SQL Server is Microsoft's enterprise-grade relational database management system used for storing, managing, and analyzing data in a wide range of applications.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: SQL Server Data Quality Services databases Target entity description: SQL Server Data Quality Services databases are a set of specialized SQL Server databases that store knowledge bases, data quality rules, and operational data used to profile, cleanse, and match data within the Data Quality Services framework.
-
A.
SSIS Catalog
SSIS Catalog is a centralized SQL Server repository and management framework for deploying, storing, configuring, and monitoring SQL Server Integration Services (SSIS) projects and packages.
-
B.
SQL Server Management Data Warehouse
SQL Server Management Data Warehouse is a SQL Server feature that collects, stores, and reports performance and configuration data from managed servers to support monitoring and analysis.
-
C.
SQL Server Integration Services
SQL Server Integration Services is a Microsoft ETL and data integration platform used to extract, transform, and load data between diverse sources within the SQL Server ecosystem.
-
D.
MSIServer
MSIServer is the Windows service that manages installation, modification, and removal of software using the Windows Installer technology.
-
E.
SQL Server
SQL Server is Microsoft's enterprise-grade relational database management system used for storing, managing, and analyzing data in a wide range of applications.
- F. None of above. chosen
Statements (44)
| Predicate | Object |
|---|---|
| instanceOf |
Data Quality Services component
ⓘ
SQL Server database type ⓘ |
| accessedBy |
Data Quality Client
NERFINISHED
ⓘ
SQL Server Integration Services NERFINISHED ⓘ |
| category | data quality technology ⓘ |
| configuredWith | DQS Configuration tool NERFINISHED ⓘ |
| developedBy | Microsoft ⓘ |
| enables |
centralized data quality rules
ⓘ
collaborative knowledge base management ⓘ re-use of data quality knowledge ⓘ |
| implementedAs | relational databases ⓘ |
| introducedIn | SQL Server 2012 NERFINISHED ⓘ |
| partOf |
Microsoft SQL Server
NERFINISHED
ⓘ
SQL Server Data Quality Services NERFINISHED ⓘ |
| persists |
cleansing results
ⓘ
knowledge discovery results ⓘ matching results ⓘ |
| relatedTo |
SQL Server Integration Services data quality components
ⓘ
SQL Server Master Data Services NERFINISHED ⓘ |
| requires |
DQS server installation
ⓘ
SQL Server Database Engine NERFINISHED ⓘ |
| runsOn | on-premises SQL Server instances ⓘ |
| securedBy | SQL Server security model NERFINISHED ⓘ |
| stores |
data quality activity logs
ⓘ
data quality projects metadata ⓘ data quality statistics ⓘ domain rules ⓘ domain values ⓘ matching policies ⓘ |
| supports |
Data Quality Services cleansing projects
ⓘ
Data Quality Services knowledge management ⓘ Data Quality Services matching projects ⓘ |
| supportsIntegrationWith | SSIS DQS components ⓘ |
| technologyStack | Microsoft SQL Server NERFINISHED ⓘ |
| usedFor |
data cleansing
ⓘ
data matching ⓘ data profiling ⓘ data quality management ⓘ storing DQS knowledge bases ⓘ storing DQS operational data ⓘ storing data quality rules ⓘ |
| usedIn |
data governance initiatives
ⓘ
enterprise data warehousing ⓘ master data management solutions ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Subject: SQL Server Data Quality Services databases Description of subject: SQL Server Data Quality Services databases are a set of specialized SQL Server databases that store knowledge bases, data quality rules, and operational data used to profile, cleanse, and match data within the Data Quality Services framework.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.