Quick Guide to Data Journalism

Karlijn Willems
Nov 7, 2016 · 10 min read

Originally published on https://www.datacamp.com/community/admin/blog/data-journalism-guide-tools

With a renewed focus on data storytelling in the data science industry, the approach to data science as a team sport, and big investigations carried out and published by data journalists, such as the Panama Papers, the 2016 U.S. Election Forecast or the Airbnb effect, the interest in data journalism is on the rise.

But what is data journalism exactly and how do you become one?

Today’s blog post will try to give more insights and answers to these questions.

Data Journalism, Data-Driven Journalism, CAR…

There are many definitions of data journalism out there and it’s hard to see the forest for the trees. Some say it’s the same as data-driven journalism (DDJ), others insist in the two being different disciplines. You’ll find quite some definitions out there.

In this article, we consider data-driven journalism and data journalism as the same discipline.

When it then comes to ‘data journalism’, you might think it’s an easy concept and that coming to a definition isn’t so hard at all. After all, data journalism is journalism done with data. But what does journalism exactly mean and what is data? According to The Data Journalism Handbook, data journalism “is the new possibilities that open up when you combine the traditional ‘nose for news’ and ability to tell a compelling story, with the sheer scale and range of digital information now available”.

However, this definition perhaps obscures the fact that data journalism is a workflow: in that sense, Mirko Lorenz’ definition, where data journalism is a “workflow where data is the basis for analysis, visualization and –most importantly- storytelling”, could be more accurate.

You’ll often see the term CAR or Computer-Assisted Reporting passing by on your journey and it’s pretty much equal to what we nowadays call data journalism. It was the “first organized, systematic approach to using computers to collect and analyze data to improve the news”, according to The Data Journalism Handbook.

How To Become a Data Journalist

Now that the context of data journalism is clear, you can start thinking about it takes to become a data journalist. The following section will give you more insight into what you need to do to become one and you will also find the outline of a step-by-step plan that you can follow to get into data journalism, including the best resources.

What Does It Take To Become A Data Journalist?

You may have read some quotes on this, such as “To become a good data journalist, it helps to begin by becoming a good journalist” (Meredith Broussard) or “Computers don’t make a bad reporter into a good reporter. What they do is make a good reporter better” (Elliott Jaspin), but what in the end do you need to become a data journalist?

According to Scott Klein, Deputy Managing Editor at ProPublica, and Co-Founder of DocumentCloud candidates should possess 1. Journalism skills, 2. Design talent, 3. Coding acumen. That seems fairly simple, but what about the educational background, and what is exactly meant with ‘journalism skills’, ‘design talent’ or ‘coding acumen’?

For what concerns the first aspect, you might think that you need a journalism degree. Scott Klein confirms that most people on his team have degrees in journalism, but it’s certainly not a prerequisite. There are examples of data journalists that have math or computer sciences background.

And it works well, also because, according to Klein, “journalism is a natural fit for mathletes who want to make the world a better place”. However, what Klein’s looking for in candidates also gives away that the educational background doesn’t necessarily play a big part, as long as you possess the three things he’s looking for.

And, going from the other side, it’s certainly possible to become a data science journalist if you haven’t got any technical background.

Whatever your background is, you’ll need to consider it in your quest to acquiring the three skills you need to become a data journalist!

And these three skills don’t come easy. Unfortunately, there aren’t a lot of universities or courses out there that can teach you all three and most people confirm that you really need to learn a lot on your own.

You can follow courses on Data Journalism Course and Big Data University or workshops taught by external data journalists, but the offer is quite scarce and doesn’t come cheap. Many trainings for professional data journalists often consist of collaborations between data and journalist teams, calling on support networks, data bootcamps, …

But mainly, it’s just about teaching yourself.

And this is where you need a step-by-step plan for yourself, complete with resources, to get where you need to be to start doing data journalism or, if you already have a job as a data journalist, to keep on educating yourself.

A Step-By-Step Plan

This step by step plan contains the first pointers in order to get started on doing data journalism. You will need to personalize this guide according to your educational background and your learning style.

Here are the eight steps that are including in the plan to become a data journalist:

1. Develop A Broad Knowledge Base

Journalists are naturally people that have to be able to adjust their skills whenever new topics come around. Furthermore, the subjects that data journalists cover can vary so much that you have to be able to cover a wide range, even wider than typical journalists.

The key to developing a broad knowledge base is probably different for everyone and depends on your learning style.

One of the ways, though, to get there is by reading, listening and watching a lot. But in the end, your attitude is probably the most important thing to get where you need to be. It’s definitely a plus if you’re curious by nature and that you have something that drives you to discover and learn new things all the time.

The broad knowledge base that is this first step designates doesn’t only cover knowledge of current affairs, but also knowledge of quantitative topics. You shouldn’t only be aware of, let’s say politics, and not know anything about statistics, because this would undoubtedly interfere with your capability to analyze political data. And let this also be one of the things that often comes back in articles is the advice of data journalists and editors: take stats classes. If you’re looking to get started, make sure to check out OpenIntro and the stats courses that DataCamp offers. Lastly, consider getting a bit more background on data journalism (for a list of articles and resources, go here).

2. Write, Write, Write

Data journalism is still about journalism and journalism is, among other things, also writing. You might think that this step is sort of negligible, but it really isn’t. Writing well is one of the things that is hard to teach and requires a lot of practice if you want to write fast and accurately, but still targeted to your audience and in the context of the medium you write in, which might be a blog, a newspaper, … It takes skill to write for an audience and not only for yourself. Whatever you think might be accessible and easy for others to read, could likely not be the case.

So make sure to take your time for this step. Luckily, there are quite some courses online with this topic so you won’t be left in the cold. For a small list, go here.

3. Learn (Some) Programming Languages

Even though you can do a lot of things with tools such as Microsoft Excel and programming isn’t a requirement to do data journalism per se, learning how to code at this (early) stage will benefit you.

Contrary to what you might expect, the goal of learning to program here is not only to make sure you can gather information but rather that you’re able to display information.

Note that the choice of a certain language here is dependent on where you want to work and what data/story you’re working on.

Some jobs as a data journalist require you to know more about web development than about gathering, transforming and modeling data and vice versa. To start, it’s probably best to have a basis in both and then develop your proficiency in whatever interests you more, since that will also play a part in which jobs you’re going to apply for.

That also explains why the skills that are most in-demand are JavaScript, CSS, and HTML. These languages are website-making languages. You could consider taking an EdX course like this one, which covers all three. Next, also skills with the Django (Python) and Ruby web frameworks are in high demand. If you’re looking to learn how to program in both, you should consider the CodeSchool courses.

Lastly, R/SAS/SPSS and Python should also be on a data journalist’s to-learn list. These languages differ from the other languages and the Django framework that has been mentioned above in that they are excellent to analyze and model data. Courses that might come in handy here are DataCamp’s Introduction to R and Introduction to Python for Data Science courses. They are tailored to beginners and take your programming skills to the next level, step by step. For SAS training, you can go here and for SPSS, you can go here.

4. Discover Data Journalism Workflow

Knowing the data journalism workflow and having a toolbox at your disposal to tackle the workflow is an essential step in your learning. There aren’t a lot of requirements to get started with this step, but most data journalists agree that you should be able to work with Microsoft Excel. So, if you have no idea about how spreadsheets work, you should make sure that you have a working proficiency with Excel before you start anything else.

If you have that basis, you can start looking into the data journalism workflow.

Very much like the data science workflow, data journalists should go through the steps of data collection, data wrangling, analysis, and data visualization and reporting.

However, the focus of this process will be less on modeling the data but will instead be more on the other steps, with a specific emphasis on reporting or storytelling.

For a list on resources that you can use to grasp the data journalism workflow, go to this page.

5. Build Your Toolbox

You need to have the right tools to tackle the data journalist workflow. Luckily, there is a wide range of tools at data journalists’ disposal. The choice for a certain tool naturally depends on the context you’re working in: a look at the job postings for data journalist teaches us that the tools can vary from job to job, and there’s also the context of the story and the data that will have some effect on your choice. Lastly, you might also have some preference for some tool because you have a good proficiency with it.

And this is where your attitude comes in.

Data journalism doesn’t require you to know how to work with everything, but you should be up to speed with what each tool can offer you and your story.

You should possess the capability to pick up skills and a willingness to learn.

For a list of tools that are often mentioned on forums such as Quora and in job postings, go to here.

6. Start Building Your Network

Data journalism is still journalism, so you can expect it to be pretty people-oriented.

Building your network will be important because that’s how you can find inspiration and mentorship. Your network will allow you to learn from the best.

Start by following some of the key people in data journalism and the industry on Twitter. For an initial list of people you can follow on Twitter, go to the original article.

In addition, you can also join data journalist groups on Reddit or LinkedIn to stay up to date with the latest news: consider following the subreddit /r/theydidthemath or /r/datasets, but also take a look at the more specific Python or R subreddits to stay up to date with the latest news. The language specific Reddit and LinkedIn groups are listed here.

Furthermore, you could also consider going to Meetups like this one, and keep an eye out for data journalism events and/or conferences in your region through the Data Driven Journalism or the European Journalism Center sites. Also, consider joining the Knight-Mozilla Open News community.

7. Continue Your Learning

Your learning will never be done. There is always so much more to discover and to do, especially when you want to start in this field or even when you already have a job.

You’ll always be learning.

For a list of additional resources, go to this page.

Start doing data journalism. Start small and start with a project on your own. Take a dataset and get started on analyzing, visualizing and reporting on the results. You can find projects on Kaggle or DrivenData. As a next step, you can start a blog. Just like those that are mentioned above. It’s a great way of showcasing your talent and a great addition to your resume. And you make sure that your results are shared with the world!

8. Go For it!

When you have gone through the previous steps, you might want to get yourself a job as a data journalist.

Some sites that might help you in your search for a job are News Nerd Jobs, Data Journalism Jobs, Indeed.com, the NICAR Listserv, Mediabistro Job Listings, Linkedin and Journajobs.

Some Last Advice

In the end, the best advice to get started on doing data journalism is that of Maarten Lambrechts: just start doing data journalism.

In addition, here are some tips from data journalists:

  • Don’t get discouraged. At start, you’ll most likely run into problems, but that’s no reason to give up. You learn data journalism by doing and this takes some time.
  • Don’t be afraid to start small. There are newsrooms out there that don’t have big data teams yet. Keep this into account.
  • Take your time. It will take some experience to judge whether a certain project is worth it. Sometimes, you will work on data and it just won’t make it as a story. Also take your time to build up your network, to learn from others, to build experience in the whole data journalism workflow.