A mid-sized bank came to the realization that poor data management was adversely affecting their efficiency as an organization. During a process re-engineering initiative, the organization became aware that countless hours were spent fixing data quality issues and performing complex, manual data processes prone to error across multiple departments. The leadership team knew they needed to resolve this issue but were not sure where to get started.

Poor data quality, largely stemming from duplicate data, manual processes and poor front-end validations, was creating delays across the organization. The leadership team recognized they did not have the internal data knowledge to resolve their data issues, but the culture supported a holistic data overhaul. A data strategy and roadmap to guide their future data structure was needed.