Why Data Scientists Should Write Books, And Why I Did.

By Kimberly Cook |Email | May 29, 2018 | 12252 Views

Okay, so generally science isn't easy to understand.

I get it. Trust me, I get it.

Scientists are paid the big bucks for a reason, and that's because a lot of people don't understand what the heck it is we do. But that's why writing is important. It helps us to understand what we do, and explain it to others so they can understand it, too.

So, why should we write?
We all have heard of bullet journals and productivity planners, right? They're so successful because writing down your thoughts and things to do is known to help you with achieving them. Taking the time to write things out helps you to be happier. It helps improve your concentration and focus, and can lower your stress levels.

Working in data science can be extremely stressful and even a very confusing field. I know, but I want others to know what exactly data science is, what a data scientist does, and why. That's why I decided to write a book. It helped me with all the things above, but it also let me learn more and improved my communication skills. (I hope.)

Communication skills cannot be learnt unless you practice them, and writing is a great way to practice, because you have to take the thoughts out of your head and put them onto a page. Or a blank document on your computer. Either or.

Writing makes you happier, more understanding, more emotional, more productive and more focused on your goals. Everybody needs that!

You need to explore your thoughts, consolidate them, quiet your mind. Writing things down helps to unravel everything you have going on in your head, and is a hugely important to understand yourself and your reality.

There have been a number of studies which outline the impact of writing and how writing helps people absorb information better. When you write, you become more in touch with your emotions and your goals.

Not only that, but writing can help you decipher data.

Writing and Data Science├?┬ó??-├?┬ó??Why, Where and How
All data is written, and everything written is data. There is no escaping that data is everywhere, all around us. Omnipresent.

As data scientists, it's important that we share this understanding and knowledge of data with everyone else, because chances are they don't know. And they should know.

Writing is how we share this knowledge. Okay, podcasts work, too but sometimes people still need to read what they've heard.

Reading lets people dip in and out of the information, digest it, make notes on it, work to improve it, and then come back to the bits they struggle with. Ultimately, they can rewrite it in their own words, so they can understand it a bit better.

As scientists, everything we do is to share knowledge. We want to discover new things, understand them, and release them into the world for other people to understand, too. We want to educate everyone.

Data science is big, huge at the moment. People who originally became computer scientists were programmers, but now there are more programmers and less data scientists. Which means that there are more people becoming data scientists, and more companies looking for more data scientists. At the moment, there is more demand than there is supply.

That's great!

But what could set you apart from other data scientists is your ability to tell a story using data. And this means you need to be able to write.

Why writing will help your career as a data scientist
What everybody needs, but might not know it, is someone who can explain their data to them. This is where your skills set you apart; not everyone who is a data scientist can accurately and effectively communicate the data they've seen to someone who doesn't fully understand data. A company needs a data scientist that can understand, analyse and use their data to increase their levels of success and productivity.

By providing people with a story to go along with their data, you are showing them why they need you, why they need to keep you around, and what it is that you do.

They know that data science is important, but they might not fully understand it. In fact, they probably don't. Most people who aren't data scientists don't understand anything much about data, just that it exists and you need to analyse it.

That's where you come in.

You can take the data, extract the pertinent information from it, make it digestible and show it to people. You can use graphs, numbers and anything else, but you need to make sure that people know what they're looking at, and why.

Of course you understand the data, you live and breathe data.

You know what goes into creating it, extrapolating it, working with it, exploring it and then, ultimately, using it. People need you to use their data to sell their product, share their knowledge, help expand on their ideas.

To keep on top of the rising tide of data analysts emerging, to stand out from the crowd, show people that you know what you're doing, and you're the best data scientist there is: tell them what exactly their data means to them and their business.

Writing is how you do that.

I wrote a book to share my expertise with other data scientists and aspiring data scientists to help them understand exactly what it is that I do.

My book has let me become more in touch with how I think about my job, how I view data and how I interact with it.

I wrote about the ways in which you can also understand data and decipher it, use it to your advantage and increase your employability...

Because writing engages your audience
Writing and creating a story with data helps to engage your audience and draws their attention to the information and story within the data. Your audience consists of people who you work with, work for, worked with, or have no idea who they are, but by creating a story about the data, from the data, you can engage with them.

Companies don't really know what their data means. They might not know what data they have, or what their data could do in terms of increasing their business. They may just view data and this long string of numbers, symbols that don't mean anything.

But it always means something. Data always means something. It can lead to understanding more about how people interact with an idea, a business model, a product. It can lead to creating new ideas, new products, and more jobs.

There has long been a perception that running a business and decision-making in a business setting is based solely on logic and reason. This isn't true.

Businesses are run by people, and people have emotions. And people engage emotionally with stories, not science.

Data storytelling is possible, and it's a way to communicate data insights through data, visuals and narrative.

By creating a narrative, the data is easier to digest, enlightens the audience to the insights it contains, their importance and also entertains the audience.

A data story both influences and drives change.

But that's only if you can share this knowledge with people. Working with data creates so many possibilities, but nothing will come of those possibilities unless you actually share the data with people in a way that they can understand it.

When you try to explain something verbally, you can often feel like your words are muddled. That you're not being very clear, and just sharing the thoughts that pop into your head.

If you write these insights down, you'll have put more time and thought into elaborating them and ensuring you communicate their meaning effectively.

Writing can build confidence.

Ultimately, writing is your friend.

In conclusion
Data science is confusing, understanding data is confusing, and knowledge needs to be shared. Basically, scientists exist to discover and share new information and new knowledge.

Everyone, everywhere creates data. That's why everyone should be able to understand data.

As a data scientist, writing will help you to not only understand yourself better, but it will add legitimacy to what you do, and will ultimately enable you to communicate better with others.

By producing something like a story from data, you create something that others can relate to, and when you can tell people what it is you do, and what data science is and how it can impact on their lives, they will understand you and your job better.

But you will too. Writing helps you to retain information, absorb it, and understand it. You will essentially become confident with your data skills.


What are you waiting for?? Go forth and write a book!

Your career and your mind will thank you for it.

As a matter of fact, if you liked this post and want to dig deeper in my book...then give it a clap + comment below with your email and the first 50 people will get a completely free copy of Confident Data Skills!

The article was originally published here

Source: HOB