Kate Strachnyi is widely known in the Data Community for her contribution in the Data Visualization and Story Telling space. One of the initiatives under her company, DATAcated conferences have been regularly gathering the best of the audience and generating the best of the content.
- How she got into Data Science
- Her top tips on creating the best stories via visualizations
- How DATAcated came into existence and what its about
- Tips to people who want to create a LinkedIn presence
I was lucky enough to uncover a role that allowed me to mainly work from home. My job was to analyze data with Tableau. That is the moment I fell in love with DATA.-Kate Strachnyi
My advice to those that want to build a presence on LinkedIn is to share their journey with frequent posts. Share your perspectives on where you are in the journey.-Kate Strachnyi
One of the most important aspects of data storytelling is knowing your audience. Make sure you have a good understanding of what the audience already knows, and what they truly care about. This will help you craft the narrative and design the visuals for the data story.-Kate Strachnyi
CK: The earlier part of your career was primarily in Finance. How did you transit into Analytics and Data Science? How has the journey been?
Kate: I graduated from college in 2009 with a degree in Finance & Investments; my goal was to work at a bank. This happened to be right at the height of the financial crisis; which meant hiring freezes across most banks. After networking and applying to several jobs, I was lucky enough to land a job selling risk management training to banks. After a year, one of the banks I was selling training to had hired me as a risk analyst. A year later, one of the Big Four consulting companies contacted me to work in their risk management & regulatory compliance practice with a focus on serving the financial services industry.
Fast forward a few years, and I was expecting my first child. This was a pivotal moment for me; I realized I no longer wanted to work in consulting and looked internally for a remote job. I was lucky enough to uncover a role that allowed me to mainly work from home. My job was to analyze data with Tableau. That is the moment I fell in love with DATA.
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CK: What inspires you about working in Data Science?
Kate: Data science is a field that continues to evolve. I love that there is always more to learn, new techniques, new tools, and technologies. The people in the data community inspire me the most.
CK: You have grown your brand to over 150K followers on LinkedIn currently. What has the strategy been? What advice would you give to someone who doesn’t have any LinkedIn presence, but wants to grow one?
Kate: It’s interesting because I never sought out to have a following on social media. I started posting around the time I was getting into data science. My initial posts were mainly around learning how to use Tableau and talking about visual best practices. I used LinkedIn & YouTube as methods of documenting what I learned. I also started something called ‘Humans of Data Science’ which included short video interviews with others in the data community.
My advice to those that want to build a presence on LinkedIn is to share their journey with frequent posts. Share your perspectives on where you are in the journey. If you are just starting out, share some of the obstacles you faced, or concepts you learned. If you are further along in your journey, you can share your unique perspectives on topics that you are passionate about. Be your authentic self and speak in your own voice. Engage with others in the community.
CK: Visualizations play a crucial role in the data space. What are the best practices you follow when creating visualizations to show the best insights in the easiest possible way?
Kate: Some common best practices for data visualization I typically share are:
- Selecting the right chart to represent the data you are working with (e.g. use a line graph to represent changes over time)
- Using color intentionally – avoid using the colours of the rainbow to simply ‘spice it up. Be strategic in which colours you select in order to effectively tell the data story.
- Reducing clutter to help the audience focus on the main takeaway (e.g removing redundant gridlines).
CK: Story Telling is an essential aspect of Data Science when it comes to socializing the analysis and results to clients. What are the most important aspects of Story Telling?
Kate: One of the most important aspects of data storytelling is knowing your audience. Make sure you have a good understanding of what the audience already knows, and what they truly care about. This will help you craft the narrative and design the visuals for the data story.
CK: How did the idea behind DATAcated spawn? How do you see it evolving in the coming years?
Kate: DATAcated means ‘dedicated’ to ‘data’. The idea came about several years ago when I was updating my LinkedIn headline to have something fun and eye-catching. Initially, it was data-cated and later was transformed into DATAcated.
The company focuses on 3 key areas – one is the DATAcated Academy – online training on data visualization best practices, as well as dashboard development across several tools. Then we have the DATAcated Conference – hosted on LinkedIn live and brings together thousands of participants; with speakers delivering 10-min lightning talks, and community partners providing fun giveaways. We also have the DATAcated media company which provides message amplification for companies that want to reach the data community.
CK: You have started hosting Podcasts recently – DATAcated On Air. What is your process of producing high-quality podcasts?
Kate: The DATAcated On Air podcast is made up of the recordings from the LinkedIn live shows. We have some amazing guests taking part in these conversations, including Bernard Marr, Kirk Borne, Cole Nussbaumer Knaflic, Mico Yuk, Alberto Cairo, and more!
CK: What are your favourite books when it comes to Non-Fictional and Data related? And why?
Kate: Can’t Hurt Me – David Goggins – truly inspirational book on doing hard things to achieve your goals. Deep Work by Cal Newport – training yourself to focus on tasks for longer periods of time.
CK: Tag one or two people in your industry who you would like to see answer these questions.
Kate: The 2 people that I’d like to tag are:
Chayan is a creative Data Scientist with an eye for details. An everyday learner and blogger, he has extreme eagerness to share knowledge and support the Data Science community. Connect with him on LinkedIn to get in touch and don’t forget to check out his Medium blogs.
Data Science | Machine Learning | Tech Blogger – upGrad
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