Building
Something Interesting?
Whether you're exploring enterprise intelligence, metadata operations, AI readiness, or regulated-industry analytics, I'd love to connect.
Mayowa Lanre-Taiwo is an enterprise data product and platform leader who designs governed operational intelligence systems for regulated and complex industries — spanning energy, utilities, and the public sector. His work sits at the intersection of enterprise architecture, data governance, and decision infrastructure, helping organizations turn fragmented data into trusted, AI-ready systems.
Years of progressive data leadership across energy, finance & public sector
Reduction in enterprise data model processing time through architectural rework
UAT model-to-bill alignment on a regulated utility billing data product
Systems Before Solutions
Every engagement begins with mapping the full data landscape — dependent systems, ownership boundaries, and downstream consumers. Governed intelligence is designed, not assembled.
Governance as a Design Principle
Data quality, lineage, and accountability are not post-delivery concerns — they are the foundational specifications. Every product I build treats governance as its primary architectural constraint.
Strategy to Delivery, Closed Loop
The gap between executive vision and engineering reality is where data initiatives fail. I operate across both layers — translating organizational intent into governed, measurable product outcomes.
Deep sector experience in regulated, operationally complex industries where data quality, auditability, and governance are non-negotiable requirements.
The foundation was laid in the field. At Chevron, early accountability for reservoir simulation data quality introduced a discipline that has shaped every role since: data integrity is not a preprocessing step — it is the upstream condition for every decision an organization can trust.
At Richardson Oil & Gas, full organizational accountability for a company-wide ERP data transition established an early leadership pattern — defining the strategy, designing the governance model, and operating with executive trust before holding an executive title. Enterprise-scale data ownership without the formal mandate, and the precedent for every role that followed.
Graduate research at University of Lagos produced the first end-to-end data product: an analytical decision platform designed to model and compare the economic efficacy of Nigeria's Petroleum Industry Act against six global fiscal systems. Full product ownership — requirements, architecture, and analytical output — before the title existed.
Across FIRS, VEE, and the BC Public Service, the scope of accountability expanded from department-founding to full product lifecycle ownership in regulated environments. The defining engagement at BC demonstrated executive-level technical authority: a critical enterprise data model's processing time reduced by 71% — from 94 minutes to 27 — through a complete architectural rework led with end-to-end ownership.
Today, three concurrent organizations anchor the executive portfolio. Bhalo Technologies holds the intellectual property and product architecture for the intelligence platform ecosystem. A18 Analytics delivers enterprise data products and AI-ready platforms across North American and global markets. LDV Consulting Ltd deploys industry intelligence solutions for energy, utilities, and public sector organizations across Nigeria and Africa.
Data & Analytics
Product & Delivery
Governance & Architecture
Leadership & Stakeholder
Discover & Map the System
Every engagement begins with understanding the full data landscape — active tables, relationships, dependencies, and bottlenecks. I draw the map before I plan the route.
Define Quality as a Feature
I establish data quality standards, governance protocols, and validation criteria before any development begins. These aren't after-thoughts — they're the product spec.
Build Iteratively with Stakeholders
Agile delivery structures the path from requirement to release — tight feedback loops between engineers, analysts, and business leads ensure the product stays anchored to organizational intent.
Measure, Monitor, Optimize
Delivery isn't the end. I establish monitoring procedures, track performance metrics, and iterate continuously — because a data product is only as good as its last refresh.
Whether you're exploring enterprise intelligence, metadata operations, AI readiness, or regulated-industry analytics, I'd love to connect.
