Transforming Data into Intelligent Decisions
We help organizations design, build, and operationalize modern analytics and AI capabilities that drive measurable business outcomes.
Who We Are
Mullen Analytics & AI Consulting partners with executives and operational leaders to develop data strategies, modernize analytics platforms, and deploy AI responsibly. We combine analytical rigor with practical execution to help organizations make confident, data-driven decisions at scale.
Focus Areas
- • AI strategy and operating frameworks
- • Data platform and pipeline modernization
- • Machine learning development and model governance
- • Decision intelligence, reporting, and business analytics
Strategy & Alignment
We clarify business priorities and identify where data and AI can drive meaningful outcomes.
Data Foundation & Infrastructure
We ensure data is reliable, accessible, and structured for decision-making and scale.
Analytics, Intelligence & Automation
We build reporting, models, and workflows that turn data into decisions and action.
Services
AI Strategy & Advisory
AI readiness, executive education, governance, and adoption roadmaps.
Data & Analytics Strategy
Enterprise data strategy, KPI frameworks, literacy, and maturity planning.
Data Engineering & Modern Data Infrastructure
Warehouse/lakehouse, ETL/ELT pipelines, cloud modernization, data trust.
Business Intelligence & Decision Intelligence
Dashboard modernization, automated reporting, self-service, ops insights.
Machine Learning & Predictive Modeling
Forecasting, segmentation, optimization, MLOps deployment and monitoring.
NLP & Workflow Automation
Text analytics, document intelligence, RPA, assistants, generative systems.
Healthcare & Life Sciences Analytics
Clinical KPIs, outcome modeling, resource planning, public health analytics.
Environmental & Geospatial Analytics
GIS risk modeling, land-use visualization, remote sensing, climate scenarios.
Product & MVP Development
Rapid prototyping, lightweight pipelines, fractional Chief Data/AI Officer.
Training & Capability Building
Workshops in SQL, Python, ML, dashboarding, storytelling, decision intel.
Selected Work
Case Study 1 — Breast Cancer Diagnosis Decision Tree Model
We developed a fully interpretable machine learning model to support early breast cancer diagnosis by analyzing tumor characteristics. The model was built from scratch and included explainable visual decision rules to support clinical reasoning.
Case Study 2 — Weather-Based Precipitation Prediction
We analyzed historical weather data and transformed precipitation type into predictive variables for logistic regression forecasting. The resulting models predicted the likelihood of rain or snow based on environmental conditions and highlighted the strongest driving factors.
Case Study 3 — Association Rule Mining for Oncology Feature Patterns
We applied the FP-Growth algorithm to identify co-occurring tumor characteristics associated with malignant cases. While no strong multi-feature patterns emerged—reflecting the complexity of cancer signals—we used the most informative features to train a transparent decision-tree classifier.