By modernizing its data architecture with Cloudera Enterprise, mBank, a leading Polish financial institution, improved query performance and gained access to data that had been previously inaccessible, enabling it to deploy new applications and improve decision making to expand its market position.
mBank S.A. is one of the leading Polish financial institutions and a member of Commerzbank Group (originally BRE – Export Development Bank). It is the fourth largest bank in Poland measured by total assets, servicing over 4.1 million retail clients and 19,562 corporate clients in Poland, and over 800,000 retail clients in Czech Republic and Slovakia.
mBank was established in 1986 and thus has underlying legacy IT systems that were no longer capable of keeping pace with the ever-increasing volumes of data. For example, data science staff were accustomed to using data from the previous day because of the time required to integrate and process data.
mBank built a modern IT infrastructure with Cloudera Enterprise that enables it to integrate data and rapidly populate its data warehouses with more than 300GB of data, with all the data sources being accessed simultaneously. Analyses and decisions can be made with the most current data, with queries completed much faster.
Additionally, mBank is building up its Data Science department to take advantage of this centralized Enterprise Data Hub.
A central data hub based on Cloudera Enterprise is helping improve performance enormously. For example, mBank reduced its daily data integration processes by 66 percent.
With this modern data architecture, mBank is also reducing its costs and beginning to provide access to, and integration of, data that had been inaccessible because of the slow legacy environment.
- Legacy IT systems were no longer capable of keeping pace with ever-increasing volumes of data; staff had to use day-old data due to time required to integrate and process the data and some data was simply inaccessible
- Apache Hadoop Platform: Cloudera Enterprise, Data Hub Edition
- Apache Hadoop Components: Apache Impala, Apache Spark
- BI & Analytic Tools: Oracle, IBM Cognos, Qlik
- ETL Tool: Informatica
- Business Intelligence
- Flat files from sources systems (mainly online bank transactional systems)
- Oracle DB
- IBM MQ
- Other native Apache Hadoop clusters
- Reduces daily data integration processes by 2/3
- Accelerates querying time by 4X
- Helps bank expand its market position with analyses on current data
- Enables deployment of new applications