inflearn logo

What does a data analyst do? [Monthly Datarian Seminar Replay | March 2022]

Is there any other profession where the perception from the outside and the actual work differ as much as a data analyst? We have prepared a March seminar for those who are curious about what data analysts actually do and what tasks they need to perform.

(4.7) 10 reviews

151 learners

Level Beginner

Course period 12 months

career-advice
career-advice
career-advice
career-advice

Reviews from Early Learners

4.7

5.0

김선영

100% enrolled

It was a useful lecture~

5.0

Jayden1116

100% enrolled

Thanks for the informative webinar :) It helped me a lot!

5.0

최가영

100% enrolled

thank you

What you will gain after the course

  • User Behavior Analysis Concepts and Cases

  • Funnel Analysis Concepts and Examples

📍 Notice

  • This lecture will be converted to a free course starting Monday, June 2, 2025. Please keep this in mind before purchasing the lecture.
  • If you have any questions, please click the 'Inquiry' button at the bottom right to leave a message.

Approximately 2,600 cumulative applicants!
Check out the much-talked-about seminar through this video.

📢 Please check before taking the course!

  • This course is a recorded video (VOD) of the "What do data analysts do?" live seminar held in March 2022.
  • It includes answers to real-time chat questions that came up during the live presentation.

In March, we will be discussing practical data analysis!
Monthly Datarian Seminar 🎤


The Datarian Seminar for March is 🔍

Is there any other profession where the gap between external perception and actual work is as large as it is for data analysts? We have prepared this March seminar for those who are curious about what data analysts actually do and what tasks they should be responsible for.

Data analysts fight with numbers every day to accelerate business growth and drive revenue. In our March webinar, we will discuss funnel analysis—one of the most widely used analytical frameworks—and user behavior data, which has often been at the 'center of debate' with questions like 'Is this data really necessary?' but has now become the 'center of data analysis.'

If you want to get hints on data analysis that delivers results, or if you are curious about the tasks data analysts frequently perform in actual companies, please check them out at the March seminar!

I recommend this to those who have these concerns ✅

  • I want to get a job or change careers to become a data analyst, but I can't figure out exactly what people in this role actually do.
  • You are working as a data analyst but feel as though you don't have your own unique edge.
  • I want to use data in my work, but I don't know where to start.
  • I want to use data for my work... but there is no data!

📺 In April, we will discuss a wider variety of data analysis methods.


March Seminar Timeline

#Part 1 - What does a data analyst do?

  • “Funnel Trivia: Useful to Know” _ Minju
  • "The Joys and Sorrows of User Behavior Data Analysis" _ Bomin

 

#Part 2 - Q&A with 4 Data Analysts (Minju, Bomin, Sunmi, Hyejeong)

 
2부에서 답하는 사전 질문 펼쳐보기


Q1. I'm curious if there is an average value for funnel analysis.

Q2. Is there a specific sequence or method you follow when analyzing user data? Or do you explore everything from all angles first to find insights?

Q3. When I interviewed the data team of a large retail company, they answered that they mainly process requests from other teams (marketing, sales, etc.). Is it inevitable that the scope of an analyst's role varies depending on the size of the company and the industry?

Q4. Please recommend books or videos that beginners can use to study methodologies like Funnel or RFM! While studying on my own, I found that theories like ML/DL are easy to find, but there aren't many lectures or books that teach analytical methods used in practice. T_T

Q5. When I'm told, ‘The core monthly metrics have dropped this month. Look at the data and find out the cause,' I don't know to what level of depth I should analyze and deliver the results.

Q6. I can do the analysis, but I find it difficult to come up with strategies. How do you respond to questions like, "I understand the analysis results and I see what the problem is... but what should we do about it?"

Q7. If you could go back several years to before you started working as a data analyst, what advice would you give yourself?

Q8. I am trying to introduce the concept of funnel analysis to an organization with almost no experience in data-driven decision-making. As the service evolves, I strongly feel the importance of customer analysis, but persuading others is not easy. ㅠㅠ What would be the easiest way for team members to experience funnel analysis?

Q9. The scope and potential impact of data-driven decision-making today (or in the future)


March Seminar
Introduction of Participants 📖

Part 1 Speaker <Minju>

After founding a co-living startup and working as an analyst at a B2B logistics startup, I am now the CEO of Datarian. I am a young entrepreneur with experience ranging from founding to exit. Since my first startup, I have constantly contemplated business funnels, and I am currently responsible for funnel design and analysis at Datarian.

Part 1 Speaker <Bomin>

A data worker at a recruitment platform. From creating data that never existed before to proposing business strategies and managing projects using data, I handle everything from A to Z that can be done with data.

Panelist <Hyejung>

I worked as a data analyst at a content platform and am now the CPO of Datarian. I am truly passionate about creating and analyzing Datarian's original content.

Moderator, Panel
<Sunmi>

After working as a data analyst at Coupang, Hyperconnect, and Kakao, I am now the CEO of Datarian. Working alongside the members of Datarian has made me believe even more in the power of data.


Expected Q&A 💬

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

Datarian website, you can find information about next month's seminar. 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?

You can view the slides on the Datarian blog. Please check the link below!
https://bit.ly/3OWz0iB


If you are curious about the live participation reviews,
check them out! 👏 👏

What was the most impressive content during the webinar?

  • By explaining not only your experience starting a business (share house) but also cases of utilizing user-experience-data analysis within a company, I was able to understand overall what a data analyst can do.
  • It was great to see how data analysis was used to solve problems, and the content regarding which points to gain insights from and focus on during the process was excellent!
  • It was impressive how you demonstrated the process of data-driven decision-making using the Funnel model.
  • I think it was easy to understand because you explained it with real-world examples, especially for those without prior data experience. haha
  • It was great that you shared what people who are not currently in the field can do from their current positions to become analysts.
  • Q&A Session (Part 2). Among those, the part where you mentioned to do analysis that actually makes money was particularly impressive.
  • At the end, I was most touched and impressed by Sunmi's discussion regarding the future of data-driven decision-making and the areas where data should not exert influence.

A word for Datarian!

  • I was a bit hesitant to join, wondering if this was targeted only at job seekers, but as a working analyst, I found many points highly relatable and enjoyed it very much. See you at the next webinar!
  • Thank you for always hosting webinars filled with such useful information.
  • I was very satisfied with both the content and the flow, as all four of you answered so passionately during the Q&A session :)
  • Thank you for always preparing such great webinars!
  • Thank you for creating so much great content :)
  • Please continue to provide great webinars in the future! Thank you always.

Recommended for
these people

Who is this course right for?

  • Those who want to get a job or change careers as a data analyst but have no idea what this role actually does.

  • Those who are working as data analysts but feel as though they don't have their own unique strength.

  • Those who want to utilize data in their work but don't know where to start

  • Those who want to utilize data in their work but do not have any data.

Hello
This is datarian

24,082

Learners

2,794

Reviews

29

Answers

4.9

Rating

36

Courses

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/

More

Reviews

All

10 reviews

4.7

10 reviews

  • starrykiss1972님의 프로필 이미지
    starrykiss1972

    Reviews 2

    Average Rating 4.5

    5

    100% enrolled

    thank you

    • jayden1116님의 프로필 이미지
      jayden1116

      Reviews 13

      Average Rating 5.0

      5

      100% enrolled

      Thanks for the informative webinar :) It helped me a lot!

      • ssssuper1109님의 프로필 이미지
        ssssuper1109

        Reviews 1

        Average Rating 5.0

        5

        100% enrolled

        It was nice to hear practitioners' opinions on data analysis.

        • coolk14431님의 프로필 이미지
          coolk14431

          Reviews 5

          Average Rating 5.0

          5

          100% enrolled

          It was a useful lecture~

          • datarian
            Instructor

            Shannon, thank you for your first review of the March webinar VOD!

        • yijuyeon928330님의 프로필 이미지
          yijuyeon928330

          Reviews 5

          Average Rating 4.8

          5

          100% enrolled

          I listened carefully. It was interesting to learn about the actual work, even if indirectly.

          datarian's other courses

          Check out other courses by the instructor!

          Similar courses

          Explore other courses in the same field!

          Free