Big Data Strategy

Big Data in India: A CxO Perspective

By Jasmine Kohli and Prerna Sharma


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At Vodafone India, we have a mature BI and analytics ecosystem which comprises of an Enterprise Data Warehouse (EDW) platform, an integrated analytics platform and we have recently set up an extension of a big data platform to analyze real time, high volume unstructured data. The volume of data available in these platforms put together is in access of 500+ terabytes.

The EDW platform has a 3NF (Third Normal Form) data model which holds the atomic business data, whereas the analytics platform stores aggregated data in dimensional models in multiple data marts each catering to a different line of business like marketing, sales, customer service, finance, etc. Around 1,300+ business users from different business functions across 23 locations pan-India access the EDW and data marts on a daily basis.

Top priorities

Being a telecom firm, we like all decisions to be based on facts rather than guess work, hence, analytics is one of the top priorities for us. Based on business needs, the following key areas have been identified as a part of analytics roadmap for our organization:

Self-Service BI: With this, business users will be empowered to create BI reports as per their requirements. This has already been rolled out to the key user segments.

CxO Dashboards on Handhelds: Business KPI dashboards will be made available to Cx Os over the handheld devices.

Big Data: The big data pilot project showed us that there is enormous value in tapping the dark data available in our organization and also outside. We have plans to take this initiative forward and include more use cases.

Network Analytics: Data available in our network assets holds tremendous amount of value and we are converting the information available in this humongous data into insights for business use.

Prescriptive Analytics: We are also working towards developing a prescriptive analytics framework. With this, we will be able to better anticipate our customer needs and cater to them.

The business case for big data

We have introduced the big data platform as an extension to our analytics environment and enabled a few use cases for our business users including: (1) Real-time triggers for gauging the propensity to international travel, first time OTT (Over the Top) applications like WhatsApp, Facebook, etc, have helped in targeting customers on a near real time with right offers. This has helped in increasing campaign conversions substantially and hence revenue. (2) Social network analytics has helped in predicting customers churn in advance based on their behavior patterns. This has enabled us to control churn in good measures. (3) Integration of unstructured data, ie, social media data has helped in generating more insights about customers, ie, preferences, hobbies, and profession which have helped in creating the right products for customers. Integration has enabled to understand customer’s sentiments which was not available earlier.

After we complemented out traditional analytics platform with the big data platform, we could do much more than ever before, including: (a) Quick identification of propensity of a customer to take certain decisions, and on a near real time provide tailored solutions to meet the customer needs. (b) Identify users who are having issues with a service and proactively address that. (c) Understand social media chatter related to our service to address any large-scale concerns and enable social media as a customer service channel.

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