Data Journalism vs Editorial Workflow

Data Journalism

By James Anditis (Journalism)

Turn datasets into stories with cleaning, analysis, and visualization workflows.

Editorial Workflow

By James Anditis (Journalism)

Manage story assignments, editorial calendars, and publishing workflows for newsrooms.

Data Journalism

• Cleans messy datasets by standardizing formats, handling missing values, and flagging duplicates
• Guides you through the full data journalism process from hypothesis to publication
• Provides templates for methodology documentation and story structure
• Connects you to major public data sources like Census Bureau, BLS, FDA, and state portals
• Handles common data problems like inconsistent dates, outliers, and similar names

Editorial Workflow

• Tracks stories through pitch, draft, edit, copy, and publish stages with clear status flows
• Creates editorial calendars showing what's publishing when and what's in the pipeline
• Provides assignment templates that spell out scope, deadlines, sources, and handoff protocols
• Manages deadlines with backward-planning timelines from publish date to reporting start
• Generates pre-publish checklists covering content, legal, metadata, and final sign-off

Reach for Data Journalism when…

• You're building a story from public datasets and need to verify your findings
• You have messy data with inconsistent formatting and missing values
• You need to explain your methodology clearly to readers
• You're looking for reliable data sources for research or reporting

Reach for Editorial Workflow when…

• You're managing multiple writers and need to track who's working on what
• You need a clear editorial calendar to plan what publishes when
• You're setting up handoff protocols between writers, editors, and copy editors
• You're training new editors on your publication's workflow and standards