This chapter lays the groundwork for a comprehensive exploration of cultural analytics, an emerging discipline at the intersection of data science and humanities. It begins with a historical overview, identifying the transition from a culture of scarcity to a culture of abundance in the digital age and the challenges and opportunities this presents for humanities research. It advocates for a paradigm shift in humanities scholarship, emphasizing the need for new methodologies to analyze and interpret the vast digital archives now accessible to researchers. It introduces the concept of “cultural analytics” as a field that utilizes computational and visualization techniques to uncover insights from massive cultural datasets that transcend the traditional divide between quantitative and qualitative methods. It goes on to explore the specifics of using the R programming language for cultural analysis, highlighting its potential due to its powerful package ecosystem and its ability to handle a variety of data types. The concept of tidy data is presented as a necessary standard for efficient data analysis in cultural analytics, with an emphasis on the “tidyverse” suite of packages that simplifies data manipulation for humanities scholars.