A natural language processing project using DataStax Enterprise Analytics with Apache Cassandra, Apache Spark, and several Python tools like Jupyter Notebooks and Pattern is illustrated through the task of determining which movie to watch by analyzing Twitter sentiment. The setup leverages the distributed nature of Cassandra for data storage and the efficient processing capabilities of Spark, integrated seamlessly in DataStax Enterprise Analytics, to handle large datasets. Sentiment analysis is performed on Twitter data to gauge public opinion, using tools like the Twitter API and various Python libraries. The project provides a practical demonstration of data analytics, showcasing how complex technologies can be harnessed simply for real-world applications, with detailed instructions available on GitHub. The installation process for these tools is straightforward, requiring basic configurations, and the setup is demonstrated on a Mac OS, but instructions are applicable to Linux machines as well. The project encourages exploration and modification of the Jupyter Notebook to discover insights beyond traditional movie rating systems like Rotten Tomatoes, illustrating the accessibility and power of data analytics.