Tag Archives: highcharts

Why I’m Becoming a Data Scientist

First  of all, this post exists because I’m currently in New York, studying the art of Data Science with Metis. It’s a 12-week boot camp focused on training us to use all the tools needed to pull insights from massive mountains of data.

I’m here because I want a job as a Data Scientist.

Usually when I say this, people respond in three ways:

  1. But I thought you wanted to be a journalist?
  2. Aren’t you getting your masters degree in journalism?
  3. What the hell is data science, and why would you want to do it?

My reasons are both philosophical and practical, so here’s a short explainer.

What is Data Science?

Our entire world is recorded in bits of information. Thanks to technology and the internet, human beings create and store more information now than at any point in the history of our species. From birth to death, our entire lives are recorded with paper documents, Google searches, emails, pictures and Facebook statuses. Every day trillions of data are created by billions of humans.

For example, this is how much information people create every minute of every day:

DataNeverSleeps_2.0_v2

That’s a monstrous amount of information, and we’re only looking at a slice! Many firms across hundreds of industries are also recording their own information, as more of our world goes digital. Thanks to constantly improving server memory, it’s cheaper than ever to save all this information, so most of this stuff is just sitting around, unused.

But what if we could use all this information?

What if the data revealed patterns? What if we could look deeply at the information and discover the who, what, where, why and how of our world, to empower people, companies and governments to make better decisions?

People are starting to do just that, and they’re already making waves. Mandatory reading, for examples: Big Data, A Revolution.

That’s data science. And it sounds hella awesome.

Why do Data Science?

While I was doing my masters degree in Data Journalism at Mizzou, I realized data scientists and data journalists are basically the same thing. We learned lots of amazing tools like D3.js, CartoDB and Highcharts to tell stories with data. One major difference is that professional data scientists have stronger backgrounds in mathematics, programming and statistics, which would seriously help data journalists. As I created data-driven projects and infographics, I thought a lot about how I could use data to tell stories. Soon enough, it wasn’t satisfying to make a chart or a graph here or there. I wanted to do something bigger with data.

I also realized my journalistic skills – analysis, research, inherent curiosity and storytelling – were a perfect fit for a job as a data scientist. This inspired me to think outside the box and join this bootcamp, where I could get the programming and statistics needed to complete my education. This Venn Diagram explains the rare and challenging mix of skills needed to be a great Data Scientist.

data science

There’s also the practical motivation: Data Science as a profession is exploding, and every industry, from entertainment to healthcare, is hiring. Demand is high, and so is the pay: the median salary of a data scientist is around $107,000. Companies are hiring people right and left. Compare that to journalism as a profession, where median salaries usually sit around $31,000 a year for newspaper reporters, and layoffs loom around every corner. The storytelling opportunities could be deeper if I was involved with data science research.

Data science is still emerging, and with it, the potential for good or evil. I want to put the skills and ethics I learned as a journalist to use in this industry, so I can help establish responsible, ethical and useful uses of data to improve our world.

That’s it, pretty much. Right now, I’m looking to join a data science team that echoes those values, so I can learn better the skills of the trade. Thanks for reading this far and letting me explain this. Every week or so I’ll be blogging here about this camp, if you’re interested in learning more.

For more on Data Science, read the groundbreaking Booz Allen Hamilton Field Guide to Data Science, online for free.

Also, yes – I’m still working on my thesis. I haven’t forgotten about you, Mizzou.

Why you should learn Dataviz now

The other weekend I sat in on a Data Visualization introductory class taught over three days by three professionals in the business: Chris Canipe of The Wall Street Journal, Andrew Garcia Phillips of ChartBall.com, and Leah Becerra of the Omaha World-Herald.

In a quick and dirty 16-hour sprint, we were introduced to programming a variety of tools, including HighCharts, D3, and various text editing software.

Using these tools, we built a basic interactive graph using raw sports data. Numbers go in, beautiful pictures come out. This stuff is cutting edge – peep some gorgeous examples here. One of Mizzou’s own used these kinds of data visualizations to win a Pulitzer, and these graphics are common at the New York Times and The WSJ.

The weekend was crazy. Basically, a whole bunch of journalism nerds got together and did nerdy journalism stuff. And it was exceedingly awesome, and you should feel bad that you missed it.

But fret not – you can learn these highly demanded skills on your own with a little determination. Here’s why (and how) you should.

1. Because it’s part of the future of journalism. Take a look at journalism’s history and you’ll notice the people on the cutting edge are always the most successful, whether it’s Ben Franklin and his printing presses or ABC and color television. Take a lesson from the greats and secure your spot in journalism’s shining future, or something like that.

2. Because it’s a wild storytelling tool that helps audiences process the internet’s infinite stores of data. Journalists are no longer “gatekeepers” – if people want to know something, they can find any information they want on the internet. The flipside? There’s so much data, so many websites, that people get turned off by the gushing stream. Data visualizations help people process and explore vast amounts of data. All you do is hold their hand through it.

3. BECAUSE YOU CAN LEARN IT ON YOUR OWN FOR FREE. Like, seriously. Programming is becoming an easy skill to learn on your own, and all the journalists who taught this course taught themselves first. Explore sites like CodeAcademy, TreeHouse, Github, and W3 schools and you could know as much as anyone with a computer science degree. For D3 specifically, start here.

4. Because if you’re a Mizzou student, we just started a data visualization club, and there might potentially be a class in the spring. Jump on it.