Why is data literacy so important?
Last updated
An IntroduIf it worked for Ection to Data Literacy
Last updated
Data journalism is a crucial component of modern-day journalism. It allows journalists to go beyond traditional reporting methods and uncover stories that might not have been possible otherwise. Data journalists use a range of tools and techniques to sift through what can seem like uncharted seas of information and find the hidden stories that lies beneath the surface. By doing this they can shed light on important issues, hold those in power accountable, and help shape public opinion.
Real-life examples:
Let's take a look at some real-life examples of how data journalism has impacted our world:
The Panama Papers: In 2016, a group of journalists worked together to investigate leaked documents from a Panamanian law firm. The data contained information on offshore accounts used by politicians, celebrities, and other high-profile individuals to avoid taxes. The investigation, which involved analyzing millions of documents, resulted in the exposure of several high-profile individuals and led to investigations in countries around the world.
Police shootings: In recent years, data journalists have used data on police shootings to uncover patterns and trends in police behavior. By analyzing data on police shootings, journalists have been able to expose instances of police brutality and hold law enforcement accountable for their actions.
Environmental issues: Data journalists have also played a crucial role in exposing environmental issues. By analyzing data on pollution, climate change, and other environmental concerns, journalists have been able to raise awareness of these issues and spur action to address them.
The key to understanding why data is important is that almost anything can be represented as a data point - and often is.
Look at this image, for example. How many data points can you see?
We can classify these balls by many data points: colour, brand, size, condition, purpose, count (how many of them) and possibly even monetary value. We might keep this data for each ball in a "record", such as a row on a spreadsheet, or on an index card.
Now read this sentence.
Mpho is 34-years-old and lives in Johannesburg, Gauteng. She works in administration for a large supermarket chain, and is married with three children.
How many data points can we extract from that sentence alone which could be used to create a record about Mpho? How many might be relevant for a data story?
All of these data points could potentially be used to create a record about Mpho, depending on the context and purpose of the record. However, for a data story, some of these data points might be more relevant than others. For example, if the data story is about the challenges faced by working mothers in South Africa, Mpho's occupation, marital status, and number of children would likely be more relevant than her location or age.
