Self-Service Data Object Suite
Dec
2024
Ongoing
Problem / Purpose
Reliance on SSRS and Tableau created a bottleneck for report creation, since only the Analytics Team had Snowflake access or technical skills. As a result, many valid data needs from other teams went unmet or were manually handled in Excel/Google Sheets.
Solution
Designed and built multiple self-service data objects covering anticipated and requested data needs for cases, calls, sales, clients, and contact details. Sourced from iSolved HRIS, PrismHR (multiple instances), Salesforce, and claim systems. Defined the database schemas, table structures, and layered data models to support scalable, efficient querying. Created cleaned, typed layers and master/reference tables using DBT and Dagster. Final objects were used for both object-based and snapshot reporting, and loaded into Google Sheets via Coefficient for self-service access.
Key Achievements / Impact
Delivered robust, scalable data architecture and self-service products that preemptively addressed cross-functional reporting needs. Greatly reduced reliance on Analytics Team and improved access to trusted data sources. Strong user adoption and positive feedback across departments.
Key Technologies / Tools Used
DBT, Dagster, SQL, Snowflake, Amazon Connect, HRIS, Salesforce, Data Product Design, Data Modeling, Schema Design, Data Architecture
Role
Data Scientist (company project)
ProService Hawaii