The option that is a common data analytics tool that is also used as an interpreted, high-level, general-purpose programming language is Python. Python is a popular and versatile programming language that can be used for various purposes, such as web development, software development, automation, machine learning, and data analysis. Python has many features and libraries that make it suitable for data analytics, such as its simple syntax, dynamic typing, multiple paradigms, built-in data structures, NumPy, pandas, matplotlib, scikit-learn, etc. The other options are not programming languages, but software applications or platforms that are used for data analytics or related tasks. SAS is a software suite that provides advanced analytics, business intelligence, data management, and predictive analytics capabilities. Microsoft Power BI is a business analytics service that provides interactive visualizations and business intelligence capabilities. IBM SPSS is a software package that offers statistical analysis, data mining, text analytics, and predictive analytics capabilities. Reference: Python For Data Analysis - DataCamp