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Data-Driven Design Without a Data Analyst [Datarian Seminar Replay | November 2025]

I have worked at seven different small startups that had neither data analysts nor user researchers, and I've stumbled through various trials and errors. I will share the many realistic challenges a UX designer can face, along with the deep insights I gained while navigating through those difficulties.

(5.0) 2 reviews

108 learners

Level Beginner

Course period 12 months

Data literacy
Data literacy
product design
product design
UX Planning
UX Planning
Data literacy
Data literacy
product design
product design
UX Planning
UX Planning
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What you will gain after the course

  • Reasons why we should work based on data

  • The first thing you must do to work based on data

  • Requirements for working based on data

  • How to collaborate with colleagues to work based on data

  • How to seize data-driven decision-making opportunities

  • The significance of these efforts by the designer

Data Analysis Seminar Conducted by Working Professionals 💡
Watch the November 2025 Seminar Replay!

📢 Please check before taking the course!

  • This course is a recorded video of the Data-Driven Design Without a Data Analyst” live seminar held in November 2025.


  • Part 2 Q&A is a Live-only session, and replays are not provided.

Datarian Seminar

In November, Data-Driven Design will be covered!

2025년 11월 데이터리안 세미나 (1)_1920

November's Datarian Seminar is 🔍

These concerns are recommended for those who have them

  • Practitioners who are told to analyze data by their superiors but don't know where to start

  • Planners and designers who are curious about design cases using data

  • Anyone who wants to solve problems based on data

  • Job seekers and working professionals who see many job postings these days mentioning "data-driven" work but don't know specifically how to do it.

  • People who are intimidated by the word 'data'

Lecture Introduction

# Data-Driven Design Without a Data Analyst

Speaker Mijin Lee (Ranran)

  • Current) Product Designer with 17 years of experience

  • Current) CEO of 77th Street Dark Horses

  • Current) Winner of the 12th Brunch Book Grand Prize, Author of 'UX was Seen at the End of Data Shoveling'


  • Starting as a web designer and becoming a product designer, I have grown like a weed while working at startups in various domains, including education, healthcare, commerce, flowers, laundry, building management, recruitment, and architecture. I run <Ranran Class> to help designers who are facing the same difficulties I once did. I help designers resolve their frustrations, regain their confidence, and learn to trust themselves.

2025년 11월 데이터리안 세미나_1부 강연_1920
2025년 11월 데이터리안 세미나_1부 강연 (2)

I have worked at seven different small startups that had neither data analysts nor user researchers, gaining a wide range of hands-on experience through trial and error. I will share the various realistic difficulties a UX designer can face, along with the deep insights gained from the process of overcoming those challenges.

We are revealing vivid real-life examples that were not included in the Brunch Book Grand Prize winner, 'UX was Visible at the End of Data Digging'!

Anticipated Q&A 💬

Q. When is the Datarian Live Seminar held? Where can I apply?

You can find information about the next seminar on the Datarian website. You can also sign up right away!

Q. Is there anything I need to prepare before listening?

None :D Anyone can listen!

Q. Is it possible to view the slides used in the seminar separately?

Please check the slides at the link below!
November Seminar Slides: https://dub.sh/uzmQ0OI

Q. Is the replay only available for Part 1 of the lecture?

Yes, a replay is only provided for the Part 1 lecture.
The Part 2 Q&A is a Live-only session, which can only be heard during the live seminar and will not be available for replay.

Curious about the
live participation reviews?
👏

What was the most memorable part of the seminar?

  • What stood out to me was the fact that a data approach considering the company's revenue structure is necessary. In a way, it's obvious, but I think it was an area that could be easily overlooked. Also, I realized that deriving the metrics I'm curious about first and then identifying which channels can provide them is a way to approach data proactively.

  • It was a great lecture that taught me how to utilize the unrefined qualitative and quantitative data at my current company to improve services, emphasizing that one must approach data from a business perspective and mindset rather than just focusing on the importance of data tools. I was able to gain some answers on what criteria should be used to classify data.

  • I knew data was important, but I was curious about how to collect and utilize it, so I liked that you explained it using practical real-world examples.

  • The need for effort in processing data before analysis, and the attitude of asking questions rather than just using the data itself, was impressive.

  • It was impressive that data should be used by asking questions rather than just looking for answers. I thought I had been asking questions of the data while working on my project, but after listening to today's lecture, it was quite shocking to realize that I had actually just been looking for answers within the data.

  • It was great to learn about the importance of data, and I liked that the overall content—such as what kind of data is needed and the best ways to extract it—was easy enough for a beginner to follow without any difficulty :)

  • It was impressive to see a practical approach to utilizing data that moved beyond the perspective of a data analyst.

  • It has always been the most difficult to divide targets and segments, and I had many concerns about what criteria to use when deriving new features tailored to those targets. Thinking according to the content you summarized, I feel that organizing ideas will now be much more logical and easier. This was the most impressive and best part.


  • It was impressive that data was viewed not just as numbers or results, but as a starting point for a deeper understanding of user behavior, and that what a designer needs is the critical thinking to ask questions rather than just analytical skills. Also, the point that timely data is more important than perfect data left a strong impression. It felt realistically relatable that when data is difficult to access or unrefined in practice, it is important to be satisfied with a reasonable level and move forward with execution.




A word for Datarian!

  • This seminar was honestly more helpful than other courses I've taken elsewhere that cost hundreds of thousands of won. Thank you so much for providing access to the know-how you've gained through years of hands-on experience at such a great price.

  • I feel like I'm always being helped because you consistently teach easy and core concepts. As I follow along step by step, I hold onto the hope that I might one day be able to walk the path of data analysis, which currently seems so vague.

  • In Korea, where the concepts of UX/UI and product design are not yet fully established, lectures like this seem very precious. Please continue to hold seminars like this often in the future.

  • It was a time to gain valuable insights. I truly support the work you are doing, and I look forward to seeing Datarian and its users grow together.

  • It was a lecture where I could really feel the effort put into delivering high-quality content. I'm so glad I finally discovered Datarian's lectures! Thank you so much!!

  • It was my first live session, and I loved it because the lecture was packed with high-quality content. While there is plenty of information about data analysis on the internet, data insights are always confusing when you actually try to organize them clearly. I liked that you explained things from a broad perspective, such as the criteria for derivation and why data is necessary. Furthermore, it was even better because the lecture provided clear standards for each target.

  • Thank you for giving me the feeling of discovering something even more fun in a world already full of fun things!

  • Thank you for always providing such great lectures!

  • The explanation was easy to understand, making complex and difficult topics feel much simpler. Additionally, I was very satisfied with the clean and concise presentation style!

  • I was feeling lost about how to analyze the data, but I was able to gain many insights through this seminar. Thank you for hosting such a great seminar!


Recommended for
these people

Who is this course right for?

  • Practitioners who have been told by higher-ups to analyze data but don't know where to start

  • Planners and designers who are curious about design cases using data

  • Anyone who wants to solve problems based on data

  • Job seekers and working professionals who see "data-driven" everywhere in job postings these days but aren't sure exactly how to do it in practice.

  • People who are afraid of the word 'data'

Hello
This is datarian

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Experienced working analysts with solid practical experience plan data analysis education and teach the lectures themselves.

If you want to learn more about Datarian

👉 https://datarian.io/

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    godrk123

    Reviews 4

    Average Rating 4.8

    5

    100% enrolled

    It was helpful for understanding what is necessary and important for making data-driven decisions!

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