Business Intelligence and Analytics Engineer with 20+ years of experience, specializing in preparing data that is consumable by BI tools, statistical models, ML algorithms and AI systems.
- Dominance analysis pipeline
- Visualization handoff
- Scalability
- Impact
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- Developed Proof-of-Concept Dashboards
- Redesigned Tableau workflows
- Owned the reengineering of a performance report
- Resolved semantic discrepancies between reporting products
- Designed and implemented a dashboard requirement template
- Established traceability dashboards
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Developed Proof-of-Concept Dashboards by engineering data for Tableau using Alteryx and R to implement business and technical requirements faster without involving resources in IT.
Redesigned Tableau workflows by converting single large datasets into multiple join-ready datasets using the new Tableau relationships feature.
Implemented Alteryx pipelines to offload complex joins from existing processes into Tableau, fostering effective data modeling practices within a previously resistant culture.
Owned the reengineering of a performance report from SAP Business Objects (BO) to Alteryx and Tableau, resolving a high-visibility customer dispute.
Resolved semantic discrepancies between two crucial container-volume reporting products, defining data-driven rules that restored metric consistency and rebuilt trust in reporting.
Designed and implemented a dashboard requirement template that revealed hidden technical scope, enabled clearer project handoffs, and empowered data-driven discussions on delivery timelines and priorities.
Established traceability dashboards that documented record-level logic and lineage, driving a 95% reduction in support cases across two critical dashboards and significantly enhancing operational efficiency.
Prepared 800+ survey datasets in R-ready formats, enabling automated dominance analysis and consistent model outputs.
Structured results for direct Tableau consumption, turning complex statistical output into accessible visuals.
Built repeatable workflows to run analyses at scale, store outputs, and maintain traceability.
Reduced manual effort and improved reliability of insight delivery to consulting and client stakeholders.
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