UniCredit powers a fast data customer insight platform with Scala and Akka Platform from Lightbend
Facing an inability to easily access and rapidly analyze decades of historical data, UniCredit’s goal was clear: unlock the value in its vast data repositories in order to understand the needs of future customers. In particular, the company wanted to uncover and graph relationships between its corporate clients, and look for patterns or connections that would help better provide services for interconnected customers.
UniCredit decided to create a new team called the Group Research and Open Innovation department, tasked with researching innovations that would power UniCredit for the future.
UniCredit’s mix of legacy data repositories and storage was standing in the way of getting a meaningful, expansive view of business customers. The challenge was to find a way to connect everything together meaningfully. The UniCredit team started off by implementing Cloudera’s Hadoop distribution and HBase, namely as a way to bring these enormous quantities of disparate data into one place.
However, to put this data into motion and make it valuable through algorithmic, graphical data analysis, this solution was insufficient. The company needed a highly performant data pipeline that would be resource-efficient and resilient, and also fun to work with and fast to prototype.
After reviewing all the requirements, the Group Research and Open Innovation team selected Scala and Akka Platform from Lightbend with Apache Spark to create a distributed, resilient, fast data processing platform. Within two weeks, a prototype application was ready to test.
The prototype platform was based on a distributed Akka cluster that helps to maintain resilience and elasticity. Written in Scala, the project heavily utilized Akka Platform technologies to support distribution across the cluster and to collect and send data from difference sources.
UniCredit tested the prototype in production for a few weeks before declaring it production-ready and launching it into the infrastructure. Soon, the insights from this project became so valuable that UniCredit decided to build a new “intelligent CRM” that other departments could integrate and utilize for large-scale analysis.
By selecting a new data streaming architecture based on Apache Spark and Akka Platform, UniCredit was able to access and analyze data sets that had never previously been connected, allowing the business to utilize decades of information and develop new services for interconnected corporate clients.
In the first several weeks of using the system, UniCredit was able to uncover relationships between its corporate customers, enabling it to understand and generate more personalized services than had ever been possible before.
Building on this initial success, UniCredit plans to use these same technologies in more systems across the enterprise. Thanks to the architecture it has built, the future addition of streaming technologies like Akka Data Pipelines and Spark Streaming are not only possible, but simple.
Convinced of the power of Spark, Scala and Akka Platform, UniCredit now has another prototype in the works to integrate these technologies with Apache Kafka. In fact, a new experiment using Akka Platform and Spark Streaming for natural language processing (NLP) has begun in order to analyze different types of content on the web.