The internet has gotten more competitive with information and more challenging for any new data professional to get discovered by a broader audience. “Show Your Work” by Austin Kleon is a handy book with tips from his experience. His advice in the book is general enough for many fields. Getting the work done isn’t the journey’s end. Your work should be your channel to get YOU self-promotion. I will explain why you should show your work and give five tips to get self-promotion as data professionals.
Many books (Storytelling with Data by Cole Nussbaumer Knaflic and DataStory: Explain Data and Inspire Action Through Story by Nancy Duarte) talk about telling stories with data. Furthermore, the storytellers should also reveal the stories behind the curtain. Readers would love to learn the stories about how you create/develop an excellent product/result from conducting use case analysis, data collection, model building, A/B testing, and business impact.
GitHub Isn't Enough for Self-Promotion as Data Professional
Many data professionals think the GitHub handle is enough to get discovered by the world. Being so good they cannot ignore you isn’t efficient today to get self-promoted.
The GitHub profile page shows your daily contributions, the repository you have worked on, and the PR you have opened. You might also have some followers and some stars on projects. It shows you are actively working on something, but your work doesn’t discuss itself. It needs a story and some narratives for your readers.
Only sharing your GitHub handle sets a barrier between you and the public. People interested in your work must explore themself in disorganized GitHub to know what those commits do. It puts readers who want to learn more in a position that is too complex to follow. That filtered out your potential followers.
Don’t be complacent about showing your work with too little guidance. Reading 1000 lines of code directly without content might work for some gurus, yet we couldn’t assume everyone has the same proficiency as you. A better way is to show your process, frame your work into a story, and offer everyone the complete picture.
Here are some thoughts after reading the book that correlates to the work I am doing that inspired me.
Tip 1: Think about the process, share the process, and document the process
Austin suggests concentrating on the process instead of the final result and using documentation to track the process. A similar idea from James Clear’s book “Atomic Habits.”
Although the final result is essential, the process gets much more weight. I used to fast forward the process impatiently to see the final result. That left some careless gaps, or the final result wasn’t correct. When I look back, if someone asked me what steps I would take to reach my final decision. I got lost in some of those questions: “How did we conclude this granularity of this fact table?”, “Why couldn’t apply logic A but use logic B instead?”, “What was the design decision of this component 1 year ago?” The answers to those questions became blurry as I ignored documentation, so some of my thoughts faded and became hard to track.
Having documents daily is a way to track things while writing them down. It motivates more ideas. When your work process is written down, your brain reconstructs and connects scatter dots, so it becomes clear what are the next steps and any mistakes that have been made before.
People would also love to learn from your process. If you have contributed to an open source project, talk about the project and the impact of your contribution, and even give step-by-step instructions on how to use the part you have contributed; take screenshots, and make a video to demonstrate it. If you create an APP, share the process you have completed, and make the demo for the unfinished projects. You share the process and give value back to the community, and people will follow and subscribe to your mailing list. It’s the perfect organic traffic!
Hiding the process and only showing the final product may astonish the world. However, your final product needs to be discovered, and sharing gives you the channel and time to be found, so don’t ignore the power of publicly showing your work progress.
Tip 2: Don't be afraid of sharing
Many people are afraid of sharing. I am one of those people obsessed with fearful thoughts: I am not an expert in the field, and I am too shy about showing what I did. What would others think about me, and would they judge me based on what I shared? Fear sets the barrier between you and your readers.
You’d need to give it a shot, and it’s easier to start with the things you are most comfortable about — from your daily work. Share some information you wish you had known before, and write a how-to tutorial for people who started in the data field. You’d need to have a stronger heart to show your work. Many people are too busy to leave any feedback. The ones who leave a comment indicating they care about your work. No matter is a compliment or criticism, that’s a good sign that your work is getting people’s attention.
Tip 3: Create a domain to show your work
From Austin’s book, if only one thing you can remember from the book, creating your domain is the one. Social media shifts popularity frequently, and usually, influencers have to adopt its rules to favor the algorithm. Owning a domain gives you more freedom to apply your rules and pick the best content for your readers. If your social media loses traffic, your impact and work will vanish. Few people use myspace nowadays, but no one can guarantee how long Facebook or Twitter will last. It’s safe and cheap to own and maintain a domain rather than rely on any social platform for the long term.
Creating a domain and establishing a website is straightforward. Primarily it’s become much easier with tools like WordPress and Elementor, which allows you to create a website by drag and drop without writing a line of code.
One exception from the list I saw is on Medium, an excellent writers-based community. Many publications are included, like Toward Data Science which has over 600K+ followers. You can also publish your work there simultaneously by leveraging Medium’s Customize Canonical Link feature.
Tip 4: Focus on high-quality content, read more, then write
The title of the section in the book for this suggestion is “Shut up and listen,” which talks about people who had less effort into reading but more energy into writing. Reading feeds writing is common for writers, but some people would bet on their luck or are conceited.
When you start, don’t think about monetization, don’t think about the number of followers, and don’t think about the branding of your posts on multiple social media. The only thing to focus on is writing high-quality content. Reading more classic books on data and reading what is posted on TDS would feed your writing as the source. High-quality content serves the long-term run as SEO plays a critical role. Writing High-quality content for a publication gives your article a shortcut to quicker optimizing SEO.
Tip 5: Teach others, and learn from teaching
Teaching is another way of learning. Teaching and learning are bidirectional. When you share your knowledge, that’s the time you find additional perspective, feedback, and ideas, those further help you learn more.
When I wrote the article Airflow Schedule Interval 101 three years ago, I wanted to teach people how the airflow scheduler works. While writing, I found that I don’t have a good understanding of the internal core of the scheduler. Then I read the Airflow scheduler source code, which helped me gain a much better insight than the Airflow official documentation could. My post became one of my best-performed articles since I provided more context with over 100k+ views and 1k claps.
I sometimes picked up some StackOverflow questions to which I didn’t know the answer. When it came to that time, I provided an answer after researching and getting my answer accepted. That’s the opportunity to learn something new and contribute back simultaneously.
“Show Your Work” only needs around 2 hours to read, but practicing his suggestion and tips could be a lifelong journey.
As data professionals, your work shouldn’t be secret to hold. I have two examples to share from my experience that show your work got me more opportunities.
- I once posted Frontpage Slickdeals Data Analysis with Pandas and Plotly Express, and I got an interview opportunity from Slickdeals.com.
- I posted another article on Alluxio on EMR: fast storage access and sharing for Spark jobs. I got the opportunity to meet with the founder and talk about my work at a local Meetup event in NYC.
If you’d like to be discovered and brand your work and yourself, Austin’s suggestion to show your work is an excellent handy book that you shouldn’t miss as data professional.
I hope my stories are helpful to you.
The airflow schedule interval could be a challenging concept to comprehend, even for developers work on Airflow for a while find difficult to grasp. A confusing question arises every once a while on StackOverflow is “Why my DAG is not running as expected?”. This problem usually indicates a misunderstanding among the Airflow schedule interval.
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