The process of streamlining data to minimize redundancy and awkward many-to-many
ID: 3788906 • Letter: T
Question
The process of streamlining data to minimize redundancy and awkward many-to-many relationships is called:
A.
data cleansing
B.
data scrubbing
C.
normalization
D.
redundancy reduction
DBMS for midrange computers include all of the following EXCEPT ____:
A.
DB2
B.
Oracle
C.
Microsoft Access
D.
Microsoft SQL Server
In clustering, a data mining tool will:
A.
find new groupings within data
B.
find related predictions from existing values
C.
find related predictions from existing values
D.
find new associations
In a relational database, a record is also called a/an:
A.
row
B.
entity
C.
field
D.
entry
Within a corporate information services department, the task of creating the physical database and its logical relations are responsibilities of the ________ function.
A.
data administration
B.
database administration
C.
data modeling
D.
server administration
Big Data does NOT refer to ____:
A.
data created by social media (i.e., tweets, Facebook Likes)
B.
datasets with fewer than a billion records
C.
datasets with unstructured data
D.
machine-generated data (i.e., from sensors)
A.
data cleansing
B.
data scrubbing
C.
normalization
D.
redundancy reduction
Explanation / Answer
The process of streamlining data to minimize redundancy and awkward many-to-many relationships is called:
Answer: Option C. normalization
DBMS for midrange computers include all of the following EXCEPT ____:
Answer: Option C. Microsoft Access.
In clustering, a data mining tool will:
Answer: Option A.
find new groupings within data
In a relational database, a record is also called a/an:
Answer: Option A. row
In a relational database, a row also called a record or tuple
Within a corporate information services department, the task of creating the physical database and its logical relations are responsibilities of the ________ function.
Answer: B.database administration
Big Data does NOT refer to ____:
Answer: B.datasets with fewer than a billion records
.
Answer: Option A.
find new groupings within data
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