Ayoade Adegbite is an analytics engineering consultant, data educator, and founder of Behind The Data. His work sits at the intersection of data engineering, analytics and AI readiness: designing scalable data pipelines, improving data quality, and transforming data into actionable business value.
He also contributes to open-source tooling. He has developed three dbt packages (dbt-doc-inherit, dbt_doc_tracker and dbt_anomaly_detector) and a VS Code extension, dbt Flow Lineage, designed to enhance data documentation, improve observability and elevate the developer experience.
Where do organisations go wrong when importing AI strategies?
The biggest mistake is copying solutions without copying context. Many advanced economies have:
- Mature data infrastructure
- Strong governance frameworks
- High-quality, well-labelled datasets
When organisations try to replicate their AI strategies without these foundations, the result is fragile systems that don’t scale. Instead of copying AI, organisations should first invest in:
- Data collection standards
- Governance policies
- Internal data maturity
How my career journey took shape
Interestingly, I didn’t start with a clear roadmap into analytics engineering. I moved from general technical problem-solving into data, initially focusing on analysis, then faced a lot of difficulties, especially around data quality. That shift pushed me deeper into data engineering and eventually into analytics engineering, where I now focus on building systems that make analytics and AI possible.
My early struggles
The biggest challenge early on was direction. The data space is filled with noise (different tools, roles and learning paths), making it difficult to know where to focus. Another major challenge was access:
- Limited structured learning paths
- Lack of mentorship
- Few opportunities to work on real-world projects
Behind The Data
That’s one key problem Behind The Data solves. It is both a consulting and a talent development company focused on building reliable data ecosystems.
On the consulting side, we help organisations design and implement data systems (pipelines, models and governance structures) that make data trustworthy and usable for decision-making.
On the talent development side, we train data professionals through practical, project-based learning, emphasising real-world scenarios rather than just theory. The goal is to produce professionals who can contribute effectively from day one.
What are Africa’s biggest data and AI opportunities in the next five years?
The biggest opportunities will be in sectors where data already exists but is underutilised:
- Financial services
- Logistics and supply chain
- Telecommunications
- Public sector systems
- Education
There’s also a major opportunity in building data infrastructure itself: pipelines, warehouses and governance systems.
As a founder, trainer and advisor, how do you balance technical expertise with leadership?
I focus on clarity and systems. Technically, I stay involved in understanding how systems are built. From a leadership perspective, I focus on:
- Setting direction
- Simplifying complexity
- Enabling others to execute
Leadership, to me, is about making systems work through people, not just doing the work yourself.
