Data journalism is a rapidly growing field that combines the traditional skills of investigative reporting with the technical skills of data analysis. By using data to uncover stories and convey insights, data journalists are playing an increasingly vital role in making sense of the world‘s complex issues.
If you‘re intrigued by the power of data-driven storytelling, data journalism may be the perfect career path for you. In this comprehensive guide, we‘ll dive into what it takes to become a successful data journalist, from the essential skills to develop to the tools and resources you‘ll need along the way.
Why Data Journalism Matters
In today‘s digital age, we‘re drowning in data. According to a report by DOMO, over 2.5 quintillion bytes of data are created every single day. By 2025, it‘s estimated that 463 exabytes of data will be created each day globally – the equivalent of 212,765,957 DVDs per day!
With so much information being generated, making sense of it all is one of the biggest challenges facing society. That‘s where data journalists come in. By analyzing datasets, uncovering patterns, and telling data-driven stories, they play a crucial role in separating signal from noise and keeping the public informed.
As data journalist Paul Bradshaw explains, "Data journalism is helping to explain the world in a way that is evidence-based, transparent, and accessible. It has the potential to empower citizens, hold the powerful accountable, and drive positive change."
The impact of data journalism can be seen in stories like the Panama Papers, which used a massive leak of financial documents to uncover global corruption, and the Pulitzer Prize-winning "Murder with Impunity" series, which analyzed unsolved homicide data to shed light on the failure of police to solve murders in major U.S. cities.
The Demand for Data Journalism Skills
As the importance of data journalism grows, so too does the demand for professionals with data skills. A 2021 report by the Google News Initiative found that 62% of news organizations globally planned to increase their investment in data journalism in the coming year.
Job postings for data journalists have also surged in recent years. According to data from the job search site Indeed, postings for "data journalist" increased by 30% from 2019 to 2020 alone. And a 2019 analysis by the U.S. Bureau of Labor Statistics predicted that employment for data-focused roles like mathematicians and statisticians would grow by 33% from 2019 to 2029, much faster than the average for all occupations.
But it‘s not just traditional news organizations hiring data journalists. A growing number of industries and roles require data-savvy communicators, from corporate communications to nonprofit advocacy to government agencies. The skills of data journalism are widely transferable and in high demand across sectors.
Essential Skills for Data Journalists
So what exactly does it take to become a data journalist? While there‘s no one-size-fits-all background, successful data journalists typically possess a combination of core journalism skills and specialized technical abilities. Here are some of the key competencies to develop:
Data Literacy
At the heart of data journalism is the ability to find, understand, and analyze datasets. Data literacy means being able to ask the right questions of data, identify patterns and outliers, and draw meaningful conclusions.
Some key data literacy skills include:
- Data sourcing: Knowing where to find relevant, reliable datasets, whether from government portals, academic sources, or using tools like web scraping and APIs.
- Data cleaning: The ability to wrangle messy, incomplete, or inconsistent data into a structured, usable format. This often involves skills like parsing data, handling missing values, and merging datasets.
- Descriptive statistics: Understanding how to calculate and interpret summary statistics like mean, median, mode, and standard deviation to describe a dataset.
- Exploratory analysis: Using visual and statistical methods to identify patterns, trends, and relationships in data. Familiarity with techniques like correlation, regression, and hypothesis testing is valuable.
Data Visualization
Effective data visualization is key to conveying the insights from data in an engaging, understandable way. Data journalists must be skilled at choosing the right chart type, designing for clarity, and telling a story with visuals.
Some important data visualization skills include:
- Design principles: Understanding visual principles like color theory, typography, and layout to create clear, compelling graphics.
- Chart types: Knowing which visualization formats (bar charts, line graphs, scatter plots, maps, etc.) work best for different types of data and story angles.
- Tools proficiency: Hands-on skills with common data viz tools like Tableau, D3.js, R, and QGIS for building interactive graphics and dashboards.
- Narrative technique: The ability to use visualizations to convey a clear finding or narrative arc, not just dump data on the page.
Programming and Computational Thinking
While not all data journalist roles require deep programming skills, a working knowledge of at least one scripting language is increasingly valuable for wrangling and analyzing data. Some common programming languages used in data journalism include:
- Python: A general-purpose language with extensive libraries for data analysis, visualization, and scraping. Key packages to know include pandas, NumPy, matplotlib, and BeautifulSoup.
- R: A statistical programming language popular for its powerful data analysis and visualization capabilities. Key packages include dplyr, ggplot2, and tidyr.
- SQL: A query language used for managing and analyzing relational databases. Useful for working with large, structured datasets.
- HTML/CSS/JavaScript: The building blocks of the web. Familiarity with these languages is useful for building interactive data visualizations and news apps.
Beyond coding proficiency, data journalists need computational thinking skills – the ability to break down complex problems, work with algorithms, and reason about data logically.
Domain Knowledge
In addition to technical skills, data journalists need deep domain knowledge in the fields they‘re reporting on, whether that‘s politics, economics, health, or education. Expertise in a particular domain helps journalists ask smarter questions, spot important trends, and provide valuable context for their audience.
Some ways to build domain knowledge include:
- Subject specialization: Focusing your education or early career on building expertise in a specific field, like business or environmental reporting.
- Continuous learning: Proactively reading industry publications, attending conferences, and taking courses to stay informed on the latest developments in your domain.
- Collaborating with experts: Partnering with academics, researchers, or subject matter experts who can provide deep insight and analysis relevant to your reporting.
Storytelling and Ethics
At the end of the day, data journalism is still journalism. The ability to tell a clear, compelling story and uphold rigorous ethical standards is just as important as technical prowess.
Key storytelling and ethics skills for data journalists include:
- Narrative writing: The ability to weave data, interviews, and background research into an engaging, cohesive story arc.
- Editing and fact-checking: A meticulous attention to detail and commitment to accuracy in all published work.
- Data transparency: Providing clear sourcing and methodology for all data used, and making raw datasets available to readers whenever possible.
- Avoiding bias: Critically interrogating datasets for biases or gaps, and using data to challenge assumptions rather than confirm them.
- Minimizing harm: Carefully evaluating the potential impacts and unintended consequences of data-driven stories on vulnerable populations.
How to Build Data Journalism Skills
Now that we‘ve covered the key skills needed for data journalism, let‘s discuss some ways to start developing them.
Formal Education
While a journalism or computer science degree can provide a strong foundation, it‘s increasingly common for data journalists to come from diverse academic backgrounds, including the social sciences, natural sciences, and humanities.
Some universities now offer specialized programs in data journalism, such as:
- Columbia University‘s M.S. in Data Journalism
- New York University‘s M.A. in Journalism with a concentration in data journalism
- University of Missouri‘s M.A. in Data Journalism
- Stanford University‘s Journalism Program with a focus on data and computational journalism
However, a degree is not the only path to building data journalism skills. Many successful data journalists are self-taught or have pieced together their education through a combination of online learning, professional workshops, and on-the-job experience.
Online Courses and Resources
For self-directed learners, there‘s a wealth of online resources available for building data journalism skills piecemeal. Some top options include:
- Coursera: Offers courses in data science, data visualization, and programming from top universities like Johns Hopkins, Duke, and University of Michigan.
- DataCamp: Provides interactive courses in data science and programming in R and Python, with a focus on hands-on learning.
- Investigative Reporters and Editors (IRE): Offers a multitude of resources and training for data journalists, including webinars, conferences, and a mentorship program.
- The Data Journalism Handbook: A free, open-source guidebook to data journalism featuring insights and case studies from leading practitioners worldwide.
- NewsLabTurkey: Aggregates a comprehensive list of free data journalism courses, tools, and resources from around the web.
The key is to start with the fundamentals – data literacy, basic stats and programming, data visualization design – and gradually layer on more advanced skills over time.
Building a Portfolio
As with any journalism job, building a strong portfolio of data-driven work is essential for landing data journalist positions. Some tips for assembling your portfolio include:
- Do data projects on your own time: Find datasets relevant to topics you‘re passionate about, and use them to report your own data-driven stories. Publishing on your own blog or platforms like Medium can showcase your skills.
- Contribute to open source projects: Many data journalism organizations make their datasets and code open source. Contributing to these projects is a great way to build your skills and network with other data journalists.
- Enter data viz competitions: Participating in data visualization challenges like Makeover Monday or the Information is Beautiful Awards can hone your design skills and get your work noticed.
- Highlight your process: In addition to polished, published pieces, consider including "behind the scenes" looks at your data sourcing, cleaning, and analysis process in your portfolio. This can demonstrate your technical workflow to potential employers.
Once you‘ve started developing your data journalism skills and portfolio, it‘s time to start thinking about your career path. While traditional newsrooms are still a major employer of data journalists, a growing number of other industries are hiring for data storytelling roles.
Some common job titles to look for include:
- Data journalist
- Data visualization specialist
- News application developer
- Investigative data reporter
- Data editor
- Computational journalist
In addition to journalism-specific roles, data journalism skills are also applicable to positions like:
- Business intelligence analyst
- Data scientist
- Public policy researcher
- Information designer
- Marketing analytics specialist
- Nonprofit communications specialist
The key is to think broadly about how your skills could be applied, and to tailor your portfolio and application materials to the specific needs of each role.
Some job hunting tips for aspiring data journalists:
- Join communities like Investigative Reporters & Editors (IRE), Hacks/Hackers, and the News Nerdery to network with data journalists and get job leads.
- Set up job alerts on platforms like JournalismJobs.com, Indeed, and LinkedIn for terms like "data journalist" and "data visualization."
- Attend data journalism conferences and workshops to learn about the latest tools and connect with potential employers.
- Don‘t neglect the power of a strong cover letter that tells the story of why you‘re passionate about and qualified for the specific role.
The Future of Data Journalism
As we‘ve seen, data journalism is a rapidly evolving field that‘s only becoming more critical in an increasingly data-driven world. Looking ahead, here are some key trends and predictions for the future of data journalism:
Increased Automation and AI
As artificial intelligence and machine learning tools become more sophisticated, they‘re likely to play a bigger role in data journalism workflows. Some potential applications include:
- Automated data scraping and cleaning tools to gather and process large datasets more efficiently
- Natural language processing algorithms to analyze large bodies of text data and identify patterns
- Predictive modeling to forecast future trends based on historical data
While these tools are unlikely to replace human journalists entirely, they may free up more time for higher-level analysis and storytelling.
More Immersive and Personalized Storytelling
With the rise of virtual and augmented reality technologies, data journalists may have new opportunities to create immersive, interactive data experiences that allow readers to explore data in more intuitive ways.
Additionally, the growth of personalized content delivery may allow data journalists to tailor their stories and visualizations to individual readers based on their location, demographics, or interests. This could make data journalism feel more relevant and engaging to diverse audiences.
Collaborative Data Journalism Networks
As data becomes more complex and global in scope, more collaborative data journalism initiatives are likely to emerge. Some examples could include:
- Data-sharing partnerships between newsrooms to enable reporting on cross-border issues
- Open data initiatives that allow journalists, researchers, and citizens to contribute to and analyze shared datasets
- Nonprofit and academic institutions providing data and computational resources to support investigative journalism
These collaborative networks could help pool scarce resources and enable more impactful data-driven reporting.
Addressing Algorithmic Bias and Equity
As machine learning and AI become more integrated into our lives, data journalists will play a vital role in investigating and communicating the potential risks and unintended consequences of these systems, particularly for marginalized communities.
This will require data journalists to develop new skills in algorithmic accountability reporting, such as:
- Reverse engineering algorithms to understand how they work
- Testing AI systems for bias and discrimination
- Reporting on the human impacts of automated decision-making in areas like criminal justice, housing, and healthcare
By combining sophisticated technical skills with rigorous journalistic ethics, data journalists can help ensure that algorithms are being used in fair and transparent ways.
Conclusion
Becoming a data journalist requires a unique blend of traditional journalism skills and cutting-edge technical capabilities. It‘s a challenging but immensely rewarding career path for those passionate about uncovering truth and making sense of an increasingly data-driven world.
While the specific tools and techniques of data journalism will continue to evolve, the core principles of using data to inform, enlighten, and empower the public will remain constant. As data journalist Alberto Cairo puts it:
"Data journalists are in the business of making the important interesting. We are in the business of helping citizens understand the world, so they can make better decisions. That‘s the essence of journalism, and it will always be relevant."
If you‘re up for the challenge of harnessing the power of data to tell important stories and drive positive change, data journalism may be the perfect fit for you. Start building your skills today – the world needs your data-driven perspective.