Data Journalism Course Modules-BAKU
  • Training Module for Data Journalism Course
  • DATA JOURNALISM IN THE NEWSROOM
  • 1. Module introduction
  • 2.The History of Data Journalism
  • 3. Definition of Data Journalism
  • 4.Case studies from Turkey and from other countries
  • Practice
  • 5.Assembling a team for a data journalism project
  • 6.Skills necessary for working with data
  • TELLING STORIES WITH VISUALIZATION
  • 1.Module introduction
  • 2.History of Data Visualization
  • 3.Definition of Data Visualization
  • 4. Basic Principles of Data Visualization
  • 5.Creating good data visualization
  • 6.Matching Data and Graph Types: Interpreting Data Visualizations
  • DATA VISUALIZATION TOOLS
  • 1.Module introduction
  • 2.Using Excel to do data journalism
  • 3.Data journalism basics with Google spreadsheets
  • 4.Simple visualization tools: Infogram, Piktochart, Workbenchdata, Flourish and datawrapper
  • 5.Data visualization: advanced visualizations using Tableau.
  • Resource
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1.Module introduction

This module builds up on the previous modules of the course and its objective is introducing students to telling stories with data visualization.

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Last updated 5 years ago

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Students will go through several examples and will find out how to tell stories with different type of visualizations and what is the main principles of data visualization, how you can create good data visualization. In addition, examples of data visualization, history of data visualization, data visualization tools will be covered extensively.

Training output: Define the core concepts of data visualization and origins of data visualization. Understand how to tell story with data visualization. Understand the methods of producing data visualization. Understanding how to match data and graph types Understand what skills necessary for working with data by reviewing case studies from all around the world. Understanding how to use excel and Google sheets for data visualization Understanding how to analyze data and create simple visualizations Introduction

July 11, 1930, Hakimiyeti Milliye Newspaper tells the readers why they should save money. Name of Graphic: "Life Hill" / Source: Geçmiş Gazete.

In this section you will see the impact, importance and development of visualization in the decision-making process. Let's say that you need to understand thousands, hundreds of thousands or millions of raw data. But your time to do it is short. You may be familiar with the data, you know the sources, maybe you already know what it is about and what to analyze. So you are not unfamiliar with the data you have available. In this case, you can proceed a little faster. But let's think otherwise. You have no idea of ​​the datasets, you get them by another team / resource and you have no idea of ​​the data. In any case, the data you will use; it affects your decision making. Therefore, before using the data set to know what to say; it will help to understand why data visualization is needed. Data visualisation must have a “mission statement”, a reason to live and a story to give all the time!

"How can you use information effectively and influence its decision-making process?" One of the important answers to this question is the data visualization itself. It enables decision-making and helps to understand a news more effectively. However, if you are not skeptical when visualizing data, it can also cause a more serious error than good. Sometimes it becomes the best confusing source. But careful visualizations can produce real solutions and activate decision-making. The best data visualization is finding clues in the dataset, discovering the findings, in other words, creating a relationship. Understanding and interpreting and observing these relationships is the key to making good decisions. Therefore, it should be noted that if the visualization is done correctly, it can mean a lot even if it is a tiny dataset. The aim of this module is to explain in detail the aesthetic, impressive and remarkable aspects of data visualization, why it is important for today, how it should be done, the methods of development, the rules of visual ethics and its limits.