Proper data visualization has solved many business problems in the past without much statistics or machine learning being involved. Even today, with so many technological advancements, applied statistics, and machine learning, proper visuals are the end deliverables for business users to consume information or the output of some analyses. Conveying the right information in the right format is something that data scientists yearn for, and an effective visual is worth a million words. Also, representing the models and the insights generated in a way that is easily consumable by the business is extremely important. Nonetheless, exploring big data visually is very cumbersome and challenging. Since Spark is designed for big data processing, it also supports big data visualization along with it. There are many tools and techniques that have been built on Spark for this purpose.
The previous chapters outlined how to model structured and unstructured data and generate...