Wireless 1, a fictitious telecom service provider, is faced with a very high customer churn rate compared to the competition. To retain subscribers the provider must proactively identify subscribers that are likely to churn, and incentivize them to stay. Due to difficulty in accessing siloed data, the marketing has had limited success.
Wireless 1 is looking for self-service methods to discover relative data and compare data assets for actionable insights. Using Informatica Intelligent Data Lake, we will show you how a data analyst used semantic search, data discovery, and self-service data preparation to rapidly discover raw data and turn it into insights.
