  Due to the significant importance of Big Data analysis, especially in
business-related topics such as improving services, finding potential
customers, and selecting practical approaches to manage income and expenses,
many companies attempt to collaborate with scientists to find how, why, and
what they should analysis. In this work, we would like to compare and discuss
two different approaches that employed in business analysis topic in Big Data
with more consideration on how they utilized Spark. Both studies have
investigated Churn Prediction as their case study for their proposed approaches
since it is an essential topic in business analysis for companies to recognize
a customer intends to leave or stop using their services. Here, we focus on
Apache Spark since it has provided several solutions to handle a massive amount
of data in recent years efficiently. This feature in Spark makes it one of the
most robust candidate tools to upfront with a Big Data problem, particularly
time and resource are concerns.
