Question 39

Big data must be analyzed using powerful analytic tools.

Analyzing big data requires advanced analytic tools due to its vast volume, variety, and velocity. These tools are essential for extracting meaningful insights from large and complex datasets.

A) Inferential statistics

Inferential statistics involves making predictions or inferences about a population based on a sample. While it is a powerful method for analysis, it does not specifically address the challenges posed by big data, which often requires more sophisticated tools capable of handling extensive datasets.

B) Small, independent data sets

Small, independent data sets can often be analyzed using basic statistical methods and do not necessitate the use of powerful analytic tools. The tools required for big data analysis are designed to manage large datasets, which makes this option incorrect in the context of the question.

C) Big data

Big data must be analyzed using powerful analytic tools because of its complex nature and sheer size. These tools are designed to process and analyze large volumes of data quickly and efficiently, enabling organizations to derive insights that would be impossible to obtain through traditional data analysis methods.

D) Data analysis results

Data analysis results refer to the outcomes derived from any data analysis process, regardless of the data size. This option does not directly pertain to the need for powerful analytic tools, as it focuses on the results rather than the data itself that requires analysis.

Conclusion

Big data is the only option that explicitly requires powerful analytic tools for effective analysis, as it encompasses significant challenges that simpler data sets do not present. Other options either relate to smaller datasets or focus on methods that are insufficient for the complexity of big data. Thus, C is the definitive correct answer.