Data Quality & Modern ICT: Building Reliable Information Systems
Master the principles of data quality and harness new information and communication technologies to build trustworthy, high-performing data ecosystems that drive real business decisions.
Perfect for: Data analysts, data engineers, IT professionals, business intelligence developers, project managers involved in digital transformation, and business leaders who work with or rely on organizational data. Prior experience with data tools or basic database concepts is helpful but not required.
Bad data costs organizations millions. Good data builds empires.
Every day, businesses make critical decisions based on data — but studies consistently show that poor data quality costs organizations an average of $12.9 million per year (Gartner). Yet most professionals working with data have never been formally taught how to assess, measure, and enforce data quality at scale. This school changes that.
In this course, you'll move far beyond spreadsheet hygiene. You'll explore the full landscape of modern Information and Communication Technologies (ICT) — from cloud data platforms and APIs to AI-driven data pipelines and real-time streaming architectures — and understand exactly how data quality principles apply at every layer. You'll learn to speak the language of data engineers, analysts, governance teams, and executives alike.
From theory to practice, without the fluff.
This isn't a surface-level overview. You'll work through real-world frameworks for data profiling, data governance, metadata management, and quality KPIs. You'll discover how emerging technologies like IoT, blockchain for data integrity, and machine learning-assisted validation are reshaping what "quality data" even means in 2024 and beyond. Every concept is grounded in practical scenarios you can apply immediately — whether you're auditing an existing data warehouse or designing a new information architecture from scratch.
Who this school is built for.
Whether you're a data analyst tired of cleaning up messy datasets, a project manager overseeing digital transformation, or a business leader who wants to stop making decisions on unreliable numbers, this school gives you a structured, technology-forward framework to take control of your data. By the end, you won't just understand data quality — you'll be able to champion it across your entire organization.
What you'll be able to do
- Define and apply the six core dimensions of data quality (accuracy, completeness, consistency, timeliness, validity, and uniqueness) to real datasets
- Audit an existing data system and produce a structured data quality assessment report with measurable KPIs
- Explain the role and architecture of modern ICT technologies — including cloud platforms, APIs, IoT, and AI pipelines — and how each introduces specific data quality risks
- Design and implement a data governance framework tailored to your organization's size and data maturity level
- Use data profiling tools and techniques to proactively detect anomalies, duplicates, and schema violations before they reach production
- Apply metadata management best practices to improve data discoverability, lineage tracking, and regulatory compliance
- Evaluate emerging technologies (blockchain, ML-assisted validation, real-time streaming) for their impact on data integrity and quality assurance
- Build a business case for data quality investment and communicate its ROI clearly to non-technical stakeholders
Curriculum
6 modules · 19 lessons
Your teacher
Olivier Mumbere Muhongya
I've spent over a decade working at the intersection of data engineering, information governance, and emerging technology — watching organizations struggle with the same preventable problem: they invest heavily in data tools but neglect the quality of the data flowing through them. I've led data quality initiatives for organizations ranging from fast-growing startups to large enterprises undergoing full digital transformations, and I've seen first-hand how the right frameworks turn chaotic, untrustworthy data into a genuine competitive advantage. I created this school because I couldn't find a course that treated data quality as the serious, technology-forward discipline it truly is — so I built one. I'm excited to share everything I know with you.
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