Data Journalism

Data can lead you to original stories, test existing assumptions, and reveal patterns that stay hidden with ordinary reporting.

‍In this practical training you learn to ‘interview’ data: asking a dataset targeted questions and translating the answers into journalistic findings.

Target audience

This training is designed for journalists, researchers, and fact-checkers who want to use data for their own stories or to support ongoing investigations. It is equally suited to beginning data journalists looking for a solid, practical foundation and to experienced journalists who want to bring more structure to their data projects. Editorial teams and organizations that regularly work with public datasets, documents, and spreadsheets will also find it useful. No spreadsheet experience is required.

What you will learn

• Finding journalistic angles in data: differences, trends, ratios, exceptions, typical cases, and correlations.
• Understanding the different types of data and how a database is structured.
• Finding, assessing, and collecting data from public sources, websites, PDFs, and your own surveys.
• Importing data using functions such as IMPORTHTML, simple web scrapers, and Tabula.
• Setting up your own dataset when usable data is not available.
• Cleaning data: removing duplicates, standardizing text and dates, splitting or merging cells, and recognizing different spellings.
• Linking datasets together using lookup functions.
• Working with formulas in Google Sheets for calculations, percentages, averages, medians, spread, and outliers.
• Analyzing datasets with filters and pivot tables.
• Investigating relationships with correlations, scatterplots, and regression lines — and understanding the boundary between correlation and causation.
• Recording your work process in a data log, so your analyses remain verifiable and reproducible.
• Visualizing data, including with Flourish.
• Carefully explaining, substantiating, and incorporating findings from data into a journalistic story.

Structure

• The training follows the complete workflow of a data journalism project: from research question and data source to analysis, visualization, and publication.
• You start with the journalistic question: exactly what information are you looking for, and what calculation or comparison can answer it?
• You then collect, import, and organize your data.
• You make the dataset suitable for analysis by identifying and correcting errors, duplicates, empty values, and inconsistencies.
• You then analyze the data using formulas, filters, pivot tables, and basic statistics.
• Finally, you translate the results into verifiable conclusions, a suitable visualization, and an understandable story for your audience.
• The training includes a reference guide explaining the work process, techniques, formulas, and tools.

Teaching method

You will get short, clear explanations of techniques and journalistic applications, followed by practical exercises in Google Sheets. You'll work with realistic datasets on topics such as wealth, life expectancy, safety, press freedom, asylum, dams, and animal trafficking, and practice journalistic questions such as who, what, where, when, how much, how often, and in what proportion.

You'll learn to analyze data using filters, pivot tables, formulas, and charts, and see demonstrations of tools for scraping, cleaning, and visualization, including Instant Data Scraper, Tabula, OpenRefine, and Flourish.

Where possible, you'll apply what you've learned directly to your own research questions or datasets.

Duration

‍Two days. The training can be offered as an open course or as an in-company training. The duration, schedule, and emphasis on specific parts can be adjusted, in consultation, to the participants' prior knowledge and needs.

‍Outcome

‍After the training you will be able to:

• Translate a journalistic research question into a workable data analysis.
• Find, import, and assess the usability of relevant datasets.
• Clean, structure, and combine data.
• Perform your own calculations and search datasets using filters and pivot tables.
• Recognize and carefully interpret trends, ratios, outliers, and correlations.
• Document your data analysis so colleagues, fact-checkers, and readers can verify your approach.
• Create a suitable chart or interactive visualization.
• Turn data into a clear, factual, and journalistically relevant story.

You will then have mastered the key techniques data journalists use in daily practice — without needing to learn to program.