Enterprise Sales and Inventory Analytics
Modern reporting experience backed by batch data engineering and business-aligned KPI definitions.
Brief
Led full-stack modernization of sales and inventory reporting with Python Dash and Plotly, backed by nightly batch pipelines and analytical APIs.
Problem
Data was distributed across operational systems and legacy reporting workflows. Stakeholders needed consistent KPI definitions, faster access, and an interface that supported high-level monitoring and detailed analysis.
Approach
I partnered with business and executive stakeholders to define KPIs, built the Dash and Plotly experience, and contributed to the data platform and API layers that made pre-aggregated analytics performant and reusable.
Highlights
- Built dashboards around business questions, KPI hierarchy, filtering, and repeatable reporting.
- Supported nightly Kafka, Airflow, Hive, and Hadoop pipelines ingesting sales and inventory data.
- Served pre-aggregated analytical datasets through Python GraphQL and REST APIs.
- Integrated MySQL and MongoDB-backed datasets for reporting workflows.
Outcome
The modernized dashboards reached 1,000+ internal users and established a scalable path from operational data to business-facing analytics.
Stack
Python, Dash, Plotly, GraphQL, REST, Kafka, Airflow, Hive, Hadoop, MySQL, MongoDB.