Case study: An innovation bank
Challenge
Our client is a bank that specializes in cutting-edge financial services for both individual and corporate clients who have requested a service to improve their operations.
The bank took pride in an impressive array of information systems and a corporate data warehouse, but over time grew concerned about the quality of the data contained within. Furthermore, only a select few technical specialists from the service organization (contractor) had access to the existing repository and primary data sources, leaving business users to rely on intermediaries to obtain necessary data sets. This resulted in a significant increase in labor costs due to the numerous intermediate links in the process.
Challenges encountered by the client:
The client has established several strategic objectives:
Solution
In order to meet the client's strategic objectives, our team has implemented several projects to address specific tasks.
The tasks we aimed to solve were as follows:
To accomplish these goals, we executed three projects.
The first project involved building a corporate warehouse based on MPP Greenplum and setting up an automated process for collecting data from primary sources of business value.
Next, we created a data and information system – a knowledge base that provides users with information on the location and meaning of specific data.
For the second project, we developed an MDM system – a toolkit for managing and monitoring data quality. Its purpose was to address issues such as missing information, duplicates, and erroneous data. This system led to the creation of the client's "Golden Record".
The "Golden Record" is the most reliable, consistent, and complete view of each company's data object (customer, product, counterparty, etc.). It contains all the attributes necessary to describe the client's profile. This data can be accessed by employees for relevant information.
Measuring and improving the quality of data in primary systems allows specialists to identify problem areas in data sources and eliminate them. To monitor the quality of data, our team formulated and described a methodology for calculating a system of indicators that was later programmed and calculated on a daily basis.
The third project involved implementing the Tableau BI analytics tool and building analytical reports. With this BI system, we provided business-relevant information in the form of interactive reports that enabled analysts and managers at various levels to make real-time decisions.
We used 16 data sources from the corporate warehouse in this project, with a planned volume of over 50 TB at the start of the project.
Technologies
The final results
Benefits for the client:
Project implementation period: 18 months.