Question
Question 1
In your role as a data professional, you examine a dataset of taxi rides to determine which hour of the day typically has the highest demand. Under which discipline does this example best fall?
Data analysis
Data analytics
Data wrangling
Data science
In your role as a data professional, you examine a dataset of taxi rides to determine which hour of the day typically has the highest demand. Under which discipline does this example best fall?
Data analysis
Data analytics
Data wrangling
Data science
Answers
GPT-4o mini
The example you provided of examining a dataset of taxi rides to determine which hour of the day typically has the highest demand best falls under **Data analysis**.
Data analysis primarily focuses on examining, cleaning, transforming, and modeling data with the goal of discovering useful information, drawing conclusions, and supporting decision-making. In this case, you are analyzing the data to identify patterns related to demand over different hours.
While data analytics is a broader term that encompasses various techniques and tools for analyzing data, the specific task you mentioned aligns more closely with the more focused scope of data analysis. Data wrangling refers to the process of cleaning and preparing data for analysis, and data science covers a broader range of disciplines, including statistics, machine learning, and programming, alongside data analysis.
Data analysis primarily focuses on examining, cleaning, transforming, and modeling data with the goal of discovering useful information, drawing conclusions, and supporting decision-making. In this case, you are analyzing the data to identify patterns related to demand over different hours.
While data analytics is a broader term that encompasses various techniques and tools for analyzing data, the specific task you mentioned aligns more closely with the more focused scope of data analysis. Data wrangling refers to the process of cleaning and preparing data for analysis, and data science covers a broader range of disciplines, including statistics, machine learning, and programming, alongside data analysis.