Most XaaS offerings in the cloud provide a discover-try-buy user experience, how to predict which users have the highest propensity to be customers, or predict customers churn, or provide service recommendations become important to the XaaS. We will present how to use Python on SaaS/PaaS to do data science driven actionable business insights.

The details include how to get progression gating issues from the funnel, how to build the solution using various SaaS offerings such as SPSS, Spark, and dashDB on IBM Bluemix, how to use PySpark to access and analyze data in dashDB through the Spark-as-a-service environment on Bluemix. Moreover, we will present how to use Python and PySpark integrated in the Jupyter notebook to predict sales leads, service recommendations and analyze churns with data science algorithms.

Take Aways:

How we do data science driven for business

• Actionable business insights through progression funnel

• Data science solution architecture using SaaS/PaaS

• Data science Survival analysis of XaaS user churn behavior analysis using PySpark, SPSS and R

• Sales leads prediction using Python

• Service Recommendation using PySpark