Data Engineering & Architecture
Design and review of data pipelines, storage strategies (row vs. columnar), and performance-aware architectures for analytics and machine learning.
Patowmack Company helps organizations connect modern data engineering, cloud platforms, and applied AI with real-world policy, operations, and strategy.
This is a temporary homepage while the full site is under development.
Patowmack Company combines academic rigor with practical consulting experience in economics, data science, and public policy. The goal is to translate complex data and technology into clear, defensible decisions.
Engagements emphasize clarity, documentation, and knowledge transfer. Deliverables are designed to be understandable by both technical and non-technical stakeholders, with particular attention to assumptions, data quality, and error structure.
Projects often include teaching components: workshops, lecture-style briefings, and written primers to help teams build durable internal capability.
Representative domains where Patowmack Company can add value.
Design and review of data pipelines, storage strategies (row vs. columnar), and performance-aware architectures for analytics and machine learning.
Practical guidance on AWS and Azure services for data workloads, including security considerations and cost-sensitive design.
Structuring applied machine learning projects, from data preparation and feature engineering to evaluation, documentation, and deployment options.
Development of academic-style case studies, workshops, and curricula to help teams and students build applied data and AI skills.
For consulting, teaching, or collaboration inquiries, please get in touch by email.
Email: info@patowmack.co
Please include a brief description of your organization and the type of work you have in mind.