Ayoade Adegbite
Data Analytics Engineer, Bredge LLC
Lagos, Nigeria
Actions
Ayoade Adegbite is an accomplished data and analytics engineer with extensive experience leveraging advanced data tools and enterprise ecosystems to deliver actionable insights across diverse industries. He designs sophisticated analytical models, ensures data integrity, and implements impactful data solutions. With a strong background in ETL processes, data visualization, and robust documentation practices, Ayoade has consistently driven significant improvements in data-driven decision-making and operational efficiency.
Ayoade’s professional journey includes notable roles such as Data Analyst Engineer at WirePick, where he achieved a 35% improvement in data integration accuracy and developed a 12% enhancement in data delivery. His expertise extends to consulting roles, where he optimized business processes and revitalized operations using advanced technologies like Airflow and dbt. Ayoade holds Tableau and Apache Airflow certifications, reflecting his commitment to continuous learning and professional growth. He has also contributed as a speaker and mentor in various data-focused events and programs. Based in Lagos, Nigeria, Ayoade continues to push the boundaries of data analytics and engineering.
Area of Expertise
Topics
Data Before AI: Building the Right Foundation for AI Readiness
AI is a top priority for businesses, but without a strong data foundation, AI efforts fail. This session highlights why data maturity must come before AI adoption, ensuring organizations don’t waste time and money on unreliable models.
Problem Statement & Relevance
Many organizations rush into AI without properly managing their data. Poor data quality, inconsistent governance, and siloed information lead to flawed AI outputs, legal risks, and lost trust.
Solutions & Insights
This talk provides a structured approach to AI readiness, covering:
- Data governance, quality, and accessibility as prerequisites for AI success
- How to assess AI readiness based on data maturity
- Real-world case studies of AI failures caused by poor data management
Key Takeaways
- Why AI adoption fails without a solid data foundation
- A step-by-step guide to building AI-ready data ecosystems
- Actionable strategies to fix data quality and governance issues before investing in AI
Driving Economic Growth with Data Observability
Data is the new oil—but without proper observability, organizations often miss opportunities for growth and efficiency. In this light talk, I will introduce the concept of data observability and explain how it can be leveraged to drive economic growth by ensuring reliable, trustworthy data across an organization’s systems.
Data observability refers to the comprehensive monitoring of your data pipeline’s health, quality, and performance. By implementing data observability, organizations can spot issues early, improve decision-making, and optimize their use of data, leading to better business outcomes and overall economic growth.
In this session, I’ll break down how data observability transforms messy, siloed, and error-prone data into a reliable asset that can fuel smarter business strategies. We’ll explore the key pillars of data observability—monitoring, alerting, tracing, and governance—and I’ll share examples of how these principles help organizations reduce costly errors, optimize resources, and uncover new growth opportunities.
This talk is for anyone interested in using data to drive business success, from tech professionals to business leaders. It’s designed to be accessible, insightful, and light—leaving attendees with a clearer understanding of how data observability can enhance decision-making and economic impact.
Data Quality = Business Success: Fixing the Hidden Errors Costing You Millions
Session Type: Talk + Q&A (30 mins)
Alignment with the Conference Theme
Data-driven organizations thrive only when their data is accurate, complete, and reliable. This session aligns with the theme by helping companies eliminate costly data errors that impact business performance.
Problem Statement & Relevance
Bad data leads to incorrect analytics, compliance risks, and lost revenue. Organizations spend millions fixing data issues manually when proactive quality measures could prevent these failures.
Solutions & Insights
This session provides a practical framework for data quality, including:
- Automated data validation techniques (Great Expectations, dbt tests)
- Common data quality pitfalls and how to avoid them
- Case studies of companies that turned around poor data practices
Key Takeaways
- How to quantify the cost of bad data and secure executive buy-in
- A data quality framework for ongoing maintenance
- How to implement automated testing and observability for reliable data
The Hidden Costs of Bad Data: How to Identify and Fix Data Debt
Data is a critical asset, but data debt and accumulating poor-quality, outdated, and inconsistent data silently erode business efficiency. This session highlights the financial impact of bad data and solutions to fix it.
Problem Statement & Relevance
Many organizations unknowingly accumulate data debt, leading to slow decision-making, compliance risks, and wasted resources. Without addressing this debt, businesses struggle with inefficient analytics and AI implementation.
Solutions & Insights
This talk introduces a structured approach to identifying and reducing data debt, including:
- Common causes of data debt and how to detect them
- Strategies for improving data hygiene through automation
- How to implement proactive data governance to prevent future debt
Key Takeaways
- Learn how to quantify and reduce data debt
- Understand best practices for sustainable data quality
- Gain insights into automation tools for preventing data deterioration
The Art of Engaging Documentation: Borrowing from Storytelling & Improv
Documentation often gets a bad reputation, seen as dry, mechanical, and difficult to navigate. But what if we could make it engaging, intuitive, and even enjoyable?
We'll explore how techniques from storytelling and improvisational theater can transform documentation from a mere set of instructions into a compelling user experience.
By borrowing from these creative disciplines, we can craft documentation that guides users naturally, anticipates their needs, and adapts dynamically to real-world use.
This talk is designed to inspire, educate, and provide actionable techniques that attendees can immediately apply to their documentation projects.
Driving Analytics with Open Source: Airbyte, dbt, Airflow & Metabase
In this talk, I’ll walk through how we built an end-to-end analytics pipeline using open-source tools ( Airbyte, dbt, Airflow, and Metabase). At Kunda Kids, we extract data from multiple sources using Airbyte OSS into PostgreSQL, transform it into business-specific data marts with dbt, and automate the entire workflow using Airflow. Our Metabase dashboards provide real-time insights, and we integrate Slack notifications to alert stakeholders when key business metrics change.
This session will cover:
- Data extraction: Using Airbyte OSS to pull data from multiple sources
- Transformation & Modeling: How dbt helps create reusable data marts
- Automation & Orchestration: Managing the workflow with Airflow
- Data-driven decision-making: Delivering insights through Metabase & Slack alerts
Building Effective Docs and Culture for Sustainability: A Data Perspective
In this talk, I will share my journey of solving real-world data challenges through sustainable documentation practices. At Wirepick Solutions, I encountered a bottleneck where critical information about our database was siloed with a single individual. The delays in retrieving this knowledge, compounded by time zone differences, significantly impacted productivity. To overcome this, I developed an internal documentation system that empowered my team to access data insights independently and improved overall efficiency.
This session will highlight the importance of building effective documentation as a sustainable practice in data projects, emphasizing how a collaborative documentation culture enhances productivity, reduces reliance on individual team members, and ensures long-term success.
Attendees will learn practical steps for creating documentation in any tech project, including data collection, tool selection, and fostering a culture where documentation is a shared responsibility. The session is not just theoretical but built on practical experience, making it highly actionable for teams and individuals struggling with similar documentation challenges.
Write The Docs Kenya Conference Sessionize Event
move(data) 2025 Sessionize Event
DevFest Osogbo 2024 Sessionize Event
Writethedocs Nigeria Conference 2024 Sessionize Event
Ayoade Adegbite
Data Analytics Engineer, Bredge LLC
Lagos, Nigeria
Actions
Please note that Sessionize is not responsible for the accuracy or validity of the data provided by speakers. If you suspect this profile to be fake or spam, please let us know.
Jump to top