19 tasks, each one witnessed by the sources that watched the job — and behind every one, a prompt you can use tonight.
You’ll start by checking email (Microsoft Outlook) and the editorial calendar (Microsoft Word or Excel). Editors assign beats and data projects — you choose a tip, pull relevant datasets, and sketch a story angle.
Most afternoons are for analysis and interviews. Use Excel to clean data and PowerPoint to show findings in an editor meeting. Evenings often mean updating a story as new data or quotes arrive and sending final copy to editors.
Learn Microsoft Excel well: sorting, filtering, pivot tables, and basic formulas are used every day for cleaning and summarizing data. Newsrooms routinely expect Excel competence for quick checks and charts.
Also practice Word for drafting stories and Outlook for source and editor communications. PowerPoint helps present findings to editors or the public. These four Microsoft Office tools cover most routine newsroom tasks.
Use AI for fast summarizing or to suggest interview questions, but always verify facts against primary sources like public data, reports, or direct interviews. AI can hallucinate — that is, invent details that aren’t true.
When AI helps with drafts, mark which parts came from AI and double-check names, numbers, and quotes. Keep source files (spreadsheets, audio) and note how you verified each claim for your editor.
According to the U.S. Bureau of Labor Statistics (BLS), about 39,250 people worked in this occupation with a median pay of $62,200 per year. The lowest 10% earned about $36,240; the top 10% made about $144,140. (Source: BLS)
Local market, employer type, and your skills with data tools and programming affect where you land in that range.
Take classes in statistics, Excel, and a basic programming course (Python or R) if possible. Practice by finding public datasets (city open data, census) and build simple projects: a spreadsheet analysis and a short written report.
Publish in a student paper or blog, volunteer for local outlets, and learn to record and transcribe interviews. Use Word and PowerPoint to package your work for editors.
A data journalist blends reporting and data work: you gather documents and interviews like any reporter, but also clean and analyze datasets and turn numbers into news. Unlike a pure data analyst, you must write for the public and verify sources.
Compared with a plain reporter, you’ll spend more time in Excel and with datasets, create graphics, and often explain methodology in the story so readers can trust the numbers.
Curiosity paired with verification: you must ask the right questions of a dataset and then prove your findings with documents or interviews. That means checking the source, method, and limitations of any data.
Practically, that shows up as careful Excel work (cleaning and checking formulas), clear writing in Word, and keeping a record in Outlook of who said what and when.