Multiple Response $($More than one answer$)$

Attributes that contribute to data quality which of the following? $($select all that apply$)$

A$)$ Accuracy

B$)$ Completeness

C$)$ Consistency

D$)$ Conformity

Which of the following are common data "wrangling" operations? $($select all that apply$)$

A$)$ Testing for duplicate records

B$)$ Testing for missing, NULL, or NaN fields

C$)$ Testing for outliers

D$)$ Testing for value$-$range compliance

Common goals of the data$-$governance board include which of the following? $($select all that apply$)$

A$)$ Continually improving the quality of data across the organization

B$)$ Establishing key performance indicators from which the board can determine and track the overall data

quality

C$)$ Reducing cost and time associated with data acquisition and cleansing

D$)$ Standardizing data$-$related practices

E$)$ Creating an environment for effective data$-$driven decision making

Clustering algorithms may differ by which of these? $($select all that apply$)$

A$)$ Performance

B$)$ Memory use

C$)$ Hardness or softness

D$)$ Data$-$set size

E$)$ Need for the analyst to specify the starting number of clusters

Commonly$-$used clustering algorithms include which of these? $($select all that apply$)$

A$)$ Connectivity algorithms, such as hierarchical clustering

B$)$ Centroid algorithms, such as K$-$means clustering

C$)$ Density algorithms, such as DBSCAN clustering

D$)$ Hybrid algorithms, such as Mcluster