Input in the Big Data and data science context diagram include:
A. IT standards
B. Data sources
C. Business strategy and goals
D. Database standards
Data science involves the iterative inclusion of data sources into models that develop insights. Dat science depends on:
A. Consistency
B. Rich data sources
C. Information alignment and analysis
D. Information delivery
E. Presentation of findings and data insights
F. All of the above
Data and text mining use a range of techniques, including:
A. Profiling
B. Application reduction
C. Association
D. Data reduction
E. Clustering
F. All of the above
The first two steps in the data science process are:
A. Define Big Data data strategy and Business Need(s)
B. Choose Data Sources
C. Develop Data Science Hypotheses and Mehods
D. Acquire and Ingest Data source(s)
Veracity refers to how difficult the data is to use or to integrate.
A. TRUE
B. FALSE
Please select the answer that does not represent a machine learning algorithm:
A. Reinforcement learning
B. Supervised learning
C. Artificial learning
D. Unsupervised learning
Machine learning explores the construction and study of learning algorithms.
A. TRUE
B. FALSE
Please select the answer that best fits the following description: Contains only real-time data
A. Batch layer
B. Speed layer
C. Serving layer
D. Real-time layer
SBA is an abbreviation for service-based architecture.
A. TRUE
B. FALSE
Data mining is a sub-field of supervised learning where users attempt to model data elements and predict future outcomes through the evaluation of probability estimates.
A. TRUE
B. FALSE
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