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Cleaning the mess How "dirty data" affects everything
In this episode, we explore why real-world data is almost never clean, and how issues like missing values, inconsistencies, outliers, and collection bias can quietly distort analytics, dashboards, and machine learning models. Through simple explanations and two real stories, we break down how “dirty data” happens and why data cleaning is one of the most important steps in any data project.
Held on: 2025-12-02 12:05 UTC
What Is Data From Raw Facts to Meaningful Insights
Episode 3 explores a simple but powerful question: what is data, really?
We walk through how raw facts become structured information, explain everyday data types and features, and show why metadata and data quality are essential before any meaningful analysis or machine learning can happen.
Held on: 2025-11-19 08:13 UTC
The Art of Understanding Data: A Friendly Intro to Statistics
Statistics is the quiet engine behind every data-driven decision. In this episode, we break down the core ideas of statistical thinking using simple, real-life examples: comparing student performance, testing marketing campaigns, understanding variation, and identifying the difference between coincidence and meaningful patterns.
Held on: 2025-11-13 08:57 UTC