Client Background
The client is a prominent Swiss consumer finance bank, offering a wide range of financial services, including credit cards, loans, insurance products, and financing solutions for both new and used cars. Due to a Non-Disclosure Agreement (NDA), further details regarding the specific company cannot be disclosed.
Challenges
Data Warehouse Compliance
The organization faced a labor-intensive process to meet data governance and regulatory requirements. Manual checks and fragmented compliance efforts slowed the data provisioning process and increased the risk of errors.
Data Availability
Teams experienced slow integration and processing of data in the warehouse. Provisioning new analytics solutions could take months to complete, delaying insights and hindering timely decision-making.
Data Quality
Frequent data issues arose from non-standardized processes. As data volume grew, the lack of consistent validation checks led to mistrust in the data and made it difficult for teams to act confidently.
Stagnation in Improvements
Overall, the complicated, manual processes created bottlenecks and hindered continuous improvement. Efforts to optimize or adopt new tools frequently stalled under the weight of compliance overhead and technical inconsistencies.
Our Solution
Automated Compliance Fulfillment
To address regulatory requirements without burdening the development process, a system of automated compliance processing was introduced. This included a script that automated all necessary compliance requirements, ensuring a compliant process.
Metadata-Driven Data Processing
By implementing automated data processing based on metadata, the team cut provisioning times for new analytics solutions from months to days. Clear standards for ingestion and transformation, alongside the implementation of a centralized data catalog, ensured consistent quality and easy discoverability of datasets.
Streamlined Changes and Testing
Automated deployments, paired with data testing, significantly reduced the risk of errors in the data used by business users. This empowered teams to move faster, quickly incorporating feedback and reacting to changing business needs.
Role Definition for IT and Business
Ensuring the right roles and responsibilities for both technical and business stakeholders bridged the gap between data ownership and usage. Business users became more invested in data accuracy, while IT gained a clearer mandate for platform maintenance and innovation.
At a Glance
Improved Decision-Making
Increased trust in data led to more confident, data-driven decisions across the organization.
Accelerated Deployment
Release cycles were reduced from quarters to months, with some changes being deployed in a matter of days.
Higher Adoption & Satisfaction
Faster response to requests and on-demand data checks boosted end-user adoption, fostering a culture of data-driven collaboration.
Scalable Governance
Automated compliance and standardized processes ensured the company could easily adapt to new regulations or internal guidelines without derailing day-to-day operations.
