Cultural Analytics refers to the use of mathematical, computational, and data visualization methods for the study of cultures. While these methods can be applied to the analysis of historical cultural artifacts and records, they are particularly appropriate for contemporary global digital culture because of its massive scale. Digital cultural expressions are born as digital fles (.txt, .pdf, HTML, JavaScript, .css, .jpg, .mov, .aiff, etc.). The traces of online behavior are also recorded in digital form. This allows researchers to start analyzing these expressions and traces right away using algorithms, bypassing the stage of digitization required for non-digital artifacts. During March-June 2016, the Culture Analytics Program at UCLA brought together 115 speakers, 40 long term (3 months) researchersin-residence and dozens of visitors. Drawing on the work that already had been going on for more than ten years, the program articulated new goals for the computational study of culture. The following text is Lev Manovich's contribution to these discussions of Culture Analytics. He is using his original (2005) term “cultural analytics” rather than “culture analytics” to emphasize that the presented views and opinions are his, and he is not trying to represent a group consensus. The interview with the author, which follows the article, helps to clarify some details of the author's theoretical views as well as the history of Cultural Analytics notion.