So much for that nostalgic phrase: “Return with us now to those thrilling days of yesteryear. From out of the past come the thundering hoof-beats of the great horse Silver. The Lone Ranger rides again!” I’m afraid that the days of judging the tenure of a motion picture by popcorn sales is as long gone as hearing the words “Hi-Yo, Silver!” on an almost daily basis.

This book covers the methods of analyzing big data in order to determine the success of a motion picture, what revenue it will bring in, and even how long it will last at a given location. Other uses include where to position movie theaters. The authors also explain big data as data designed to contain three measures, the three Vs: volume, velocity, and variety.

The focus of movie analytics differs from information technology (IT) analytics in that movie analytics seeks to use the information gleaned from the collected data while IT analytics seeks to find better ways of processing data.

The two main parts of the monograph cover the logistics and methods of accessing big data, and secondly focus on the information most salient to the film industry. The content is sophisticated and not meant for the amateur or casual reader.

However, the monograph concludes with two very readable sections on Oscar prediction and the question of movie success prediction from Twitter and movie review data. The material is technical in nature and meant for the gifted statistician. Although the book is classified as a “SpringerBriefs” text, it will be most enjoyed by professional statisticians engaged in success prediction.