Banking & Finance (a major French commercial bank)
Challenge
Building a data lake for an instant payment project
Solution
Design and implementation of the data lake architecture;
Implementation of data pipelines using Hadoop ecosystem technologies;
Development of the data storage layer using Cassandra;
Setting up the data visualisation and analysis platform with ELK;
Technical environment: the project was developed using the Hadoop, Java, Cassandra and ELK ecosystem. It was implemented in a hybrid cloud environment.
Technologies
Java
Springboot
ELK
HDFS
Kafka
Spark
Cassandra
Keys to success
Mastery of the Hadoop ecosystem: our expertise in data processing and storage technologies, particularly Hadoop, enabled us to design and implement a reliable and scalable system for the bank's data lake;
Use of hybrid cloud: we implemented a hybrid cloud architecture to enable the bank to deploy large-scale data processing and analysis services quickly and easily. This approach optimised costs while guaranteeing data security and compliance;
Close collaboration with business teams: we worked closely with the bank's business teams to understand their data processing needs and goals. This collaboration resulted in the creation of a data lake tailored to the bank's needs in terms of performance, capacity and functionality, and facilitated the adoption of the solution by end users.
Industry
Banking & Finance (a major French commercial bank)
Challenge
Building a data lake for an instant payment project
Solution
Design and implementation of the data lake architecture;
Implementation of data pipelines using Hadoop ecosystem technologies;
Development of the data storage layer using Cassandra;
Setting up the data visualisation and analysis platform with ELK;
Technical environment: the project was developed using the Hadoop, Java, Cassandra and ELK ecosystem. It was implemented in a hybrid cloud environment.
Technologies
Java
Springboot
ELK
HDFS
Kafka
Spark
Cassandra
Keys to success
Mastery of the Hadoop ecosystem: our expertise in data processing and storage technologies, particularly Hadoop, enabled us to design and implement a reliable and scalable system for the bank's data lake;
Use of hybrid cloud: we implemented a hybrid cloud architecture to enable the bank to deploy large-scale data processing and analysis services quickly and easily. This approach optimised costs while guaranteeing data security and compliance;
Close collaboration with business teams: we worked closely with the bank's business teams to understand their data processing needs and goals. This collaboration resulted in the creation of a data lake tailored to the bank's needs in terms of performance, capacity and functionality, and facilitated the adoption of the solution by end users.
