DT PH II Practice 1 is designed to assess understanding of data management principles, focusing on data quality, processing, and tools. It evaluates the transition of data to information and emphasizes best practices in data quality management.
True
False
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False
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False
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False
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False
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False
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True
False
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False
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True
False
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True
False
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True
False
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True
False
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False
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Conversion
Mark-Up
Extraction
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True
False
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True
False
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System Hierarchy
User Hierarchy
None
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True
False
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True
False
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A. OLAP Metadata
B. Reporting Metadata
C. Data Mining Metadata
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Business
Product
Customer
None of the above.
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True
False
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True
False
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Multidimensional Clusters
Clusters
Blocks
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Input Structure(DLL file)
Output structure (DLL file)
Parameter file (PAR file)
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Abort
Compiled
Compiled
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Locked
Limited
Entry point
Filtered
All the options
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Volume
Accuracy
Consistency
Integrity
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Parameter file (PAR).
Output structure (DLL file)
Input structure (DLL file)
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Careless / Inaccurate data entry
No stringent rules or processes followed to validate the data entry
Lack of Master Data Management strategy
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Attribute qualification and metric qualification only
Attribute qualification and report as filter only
Attribute qualification, report as filter and relationship filter only
Attribute qualification, metric qualification and relationship filter only
Attribute qualification, metric qualification, report as filter and relationship in any combination
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Attributes
Facts
Hierarchies
All the options
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4 KB
2 KB
8 KB
16 KB
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2 CPU
4 CPU
18 CPU
No Limit
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Data de-duplication
Cleansing
Enrichment
None
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User
CPU
Memory
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Data profiling
Data cleansing
Data enrichment
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Base resource changes
If two sources merges together
Base source is deleted
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Not Possible
Yes Possible
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Acquisition
Application
Cleanup
None
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No Limit
One
Two
Three
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Data Quality Tools
Data Profiling Tools
Metadata Tools
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Fixing data quality issues in ETL
Fixing data quality issues in ODS
Fixing data quality issues in Source
Fixing data quality issues in DW
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Delete the original values since they consume space
Keep the original values in trail tables
Do not disturb the original values and place the new values in new tables
None
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Set stringent rules in validation process; if not, then in ETL process
De-duplication
Provide feedback about quality of data to source and ask source to correct and resend them
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Stage variable then Constraints then Derivations
Derivations then Stage variable then Constraints
Constraints then Derivations then Stage variable
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2
5
1
No such rules
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True
False
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