Data Literacy for Problem-Solving

In this episode, we take a deep dive into distribution analysis — a critical concept in descriptive analytics that helps us understand how data is spread, not just where its average lies. We explore the most common types of statistical distributions, where they appear in real-world processes, and the practical methods used to identify them. This discussion also ties directly back to the previous t...

An average tells us the center of the data — but it doesn’t tell us how reliable that number really is. In this episode, we explore variance and standard deviation , two fundamental concepts in descriptive analytics that reveal how much data varies around the mean. A dataset with a small standard deviation behaves consistently and predictably, while a larger one signals volatility, uncertainty, an...

In this episode, we move into the analysis stage of the analytics process, beginning with descriptive analytics. One of the most fundamental tools in descriptive analysis is the average. But what does an average really represent? In this episode, we unpack the idea of an average as our best estimate of a typical value when limited information is available. We also explore the common traps of relyi...

Turning data into measurable organizational value through strategic alignment and capability development. This episode is based on a talk delivered by Melvon Ekandjo at Henley Africa business school in Johannesburg, South Africa.

This episode explores the ETL concept. It is used to connect the analysis tool to the data source and automated the flow of data to produce consistent quality data.

The planning phase of a data project begins with forming a series of hypotheses, i.e., questions to confirm. A helpful way is to brainstorm the various ways in which a problem can manifest. We introduce mind maps to visualize the problem and the related measures to look at. Confirmatory analysis will be used at a later to confirm if the hypotheses are valid in contributing to the problem. The main...

In this episode we discuss how to ask questions that deliver actionable insights that are useful for decision making.

In this episode, we dive into the data analytics process, breaking down the journey from problem identification to actionable insights into five essential steps.

In this episode, we explored the four levels of data analytics: descriptive, diagnostic, predictive, and prescriptive. Descriptive analytics helps us describe what's happening, like analyzing sales reports. Diagnostic analytics asks why things are happening, looking at factors influencing trends. Predictive analytics predicts the future based on past data, such as predicting employee performance w...

In this episode, we explore the concept of data, from ancient forms like cave drawings to modern digital formats such as pictures, emojis, and social media posts. We discuss how digitization has revolutionized data handling and why data literacy is essential in today's information age. Join us as we uncover the value of data and its significance in our daily lives.