Hi, I’m Ruslan Smakov I specialize in building analytics and AI-driven systems that translate business problems into scalable data solutions.
Analytics Consultant with 10+ years of experience delivering business-facing analytics and data enablement initiatives across enterprise environments.
I specialize in translating complex business requirements into structured KPI frameworks, scalable data models, and executive-ready reporting layers. My focus is not just building datasets — but designing analytics environments that drive measurable operational impact.
Core Expertise:
• Business Intelligence & KPI Strategy
• SQL-Centric Data Warehousing (Star Schema, Fact & Dimension Modeling)
• Reporting Layer Architecture & Metric Standardization
• Databricks Lakehouse (Bronze–Silver–Gold)
• Data Validation, Reconciliation & Metric Governance
What I Deliver:
• Design of structured KPI frameworks aligned with business objectives
• Development of analytics-ready data marts for BI and executive reporting
• Implementation of SQL-driven warehouse models supporting operational analytics
• Construction of Bronze–Silver–Gold Lakehouse pipelines for BI consumption
• Data quality controls ensuring metric consistency and reporting reliability
• Alignment between business stakeholders and technical data teams
I build analytics systems that connect business strategy with reliable, production-ready data foundations.
Selected Projects
🟢 AI Sales Call Intelligence AI pipeline that converts unstructured sales calls into structured business signals (objections, intent, company insights) using LLM (phi3), with normalization, storage, and analytics.
Key Concepts:
- LLM-based information extraction
- Handling noisy model outputs (JSON parsing)
- Data normalization into business categories
- End-to-end pipeline (LLM → DB → Analytics)
https://github.com/smakov-data/ai-sales-call-intelligence
🟢 AI Dispatch Decision System AI-powered logistics decision system that simulates a pharmacy delivery network, evaluates operational risk, and generates dispatch recommendations using state vector modeling and an interactive Streamlit dashboard.
Key Concepts Demonstrated:
- Operational AI decision systems
- State vector modeling for system monitoring
- Risk scoring and confidence evaluation
- AI-assisted operational recommendations
- Synthetic logistics network simulation
- Real-time monitoring dashboards
- Modular decision engine architecture
https://github.com/smakov-data/ai-pharmacy-dispatch-system
🟢 FMCG Databricks Lakehouse
End-to-end analytics platform designed to support KPI monitoring, BI dashboards, and executive reporting.
Highlights:
- Lakehouse architecture (Delta Lake, Bronze–Silver–Gold)
- Batch ingestion of structured CSV data from AWS S3
- Full and incremental data loads
- Dimensional modeling (facts & dimensions)
- Gold-layer analytical views for BI consumption
https://github.com/smakov-data/fmcg-databricks-lakehouse
🟢 SQL Retail Data Warehouse
SQL-centric analytics data warehouse designed for sales analytics and reporting use cases.
Highlights:
- Star schema design (Sales Data Mart)
- Fact & dimension modeling
- Business-aligned analytical queries
- BI-ready datasets for reporting and ad-hoc analysis
https://github.com/smakov-data/sql-retail-dwh
💼 Professional Background
Background includes supporting enterprise analytics and data platforms across large-scale retail environments, working closely with data engineers on ingestion pipelines, data models, and data quality validation for reporting and analytics.