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Data Science

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Data Analysis

The Start of Persuasion: How to Properly Present Data [Monthly Datarian Seminar Replay | May 2022]

Are you having trouble persuading others with data? Learn how to present your data simply and powerfully using Google Sheets!

(4.2) 9 reviews

118 learners

Level Beginner

Course period 12 months

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What you will gain after the course

  • How to write data reports with Google Sheets

  • How to effectively communicate data analysis results

  • Know-how for persuading others with data

  • Common mistakes in data visualization and how to improve them

📍 Notice

  • This lecture will be converted to a free course starting Monday, June 2, 2025. Please keep this in mind before paying for 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!
Meet the much-talked-about seminar through video.

📢 Please check before taking the course!

  • This course is a recorded video (VOD) of the "The Beginning of Persuasion: How to Properly Present Data" live seminar held in May 2022.
  • It includes answers to real-time chat questions that came up during the live presentation.
  • The video of Gung-geum-i's lecture in Part 1 is not provided; only the lecture materials (PPT) are available.

In May, we're talking about data visualization!
Monthly Datarian Seminar 🎤

The Datarian Seminar for May is 🔍

Recommended for those with these concerns ✅

  • I've tried creating charts with data, but I'm not sure if I'm doing it well.
  • I need to create a data analyst portfolio, but I'm at a loss as to how to present the analysis results.
  • I'm curious about how to write a data analysis report that is intuitive and effective for persuasion.
  • What makes for good data visualization? It might vary depending on the situation, but I'd like to know some general standards.

📺 In June, we will share the career concerns of data analysts.

May Seminar Timeline ⏰

#Part 1 - The Beginning of Persuasion: How to Properly Present Data

✔ "Data Visualization Story"

  • Speaker Goonggeumi - A 25-year veteran engineer and UX designer / currently working at pxd. I have a keen interest in data visualization and interaction design.
  • The video for Part 1 of Speaker Gunggeumi's lecture is not provided; only the lecture materials (PPT) are available.

We introduce how to visually represent data correctly without distortion.
I would like to talk about the things to consider when trying to capture numbers through color, shape, arrangement, and movement.

✔ "Creating Reports with Data using Google Sheets"

  • Speaker Sunmi Yoon - 7th-year data analyst / Currently working at Datarian after stints at Coupang, Hyperconnect, and Kakao.

🤯 I've done the data analysis, but persuasion is hard...
We will talk about the know-how on how to effectively communicate data analysis results and persuade others. If you are someone who needs to persuade your boss, colleagues, or clients with data, please pay attention to this presentation!

#Part 2 - Q&A

2부에서 답하는 사전 질문 펼쳐보기


Q1. Why do we do visualization? Is it just to please the eyes?

Q2. When visualizing analysis outputs, to what extent should they be made aesthetically pleasing?

Q3. Do you design the narrative after final confirmation of the data results? Or do you set a desired direction first and then prepare supporting data to match it? What are some tips for data interpretation that lead to action plans and insights, rather than just listing data?

Q4. I need to create a data analysis portfolio, but I'm at a loss as to how to present the analysis results.

Q5. As someone preparing for a job, I'm not sure what I should learn. Some lectures say PowerBI is widely used in the field, others say Tableau is used more, and some even say I should just focus on mastering Google Sheets visualization. Which visualization tool should I prioritize learning to be most helpful?

Q6. Is it common to visualize using Python libraries without utilizing BI tools? I use matplotlib or seaborn for visualization, but it takes more effort than expected, so I often find myself just pulling charts from Excel when I'm in a hurry. Is this due to my lack of Python skills...? Or do others also find using Excel more efficient?

Q7. Are there specific rules for which graphs to use in different analytical situations? Also, have you ever had an experience where you escaped a situation by slightly overstating or understating data through graphs?

Q8. Is there such a thing as a persuasive dashboard? C-level and internal dashboards seem like they would be different—what points should be prioritized for each?

May Seminar
Participant Introduction 📖

Part 1 Speaker <Gunggeumi>

I am working as an engineer and UX designer at pxd. I am highly interested in data visualization and interaction design.
* For Part 1, the video of the speaker's lecture will not be provided; only the lecture materials (PPT) will be provided.

Part 1 Speaker <Sunmi>

Having worked as a data analyst at Coupang, Hyperconnect, and Kakao, I am now the CEO of Datarian. Working alongside the members of Datarian has led me to believe even more strongly in the power of data.

Panelist <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 a company to its exit. Since my first startup, I have constantly contemplated business funnels, and I am currently responsible for funnel design and analysis at Datarian.

Panelist <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 <Hyejeong>

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

Frequently Asked Questions Q&A 💬

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

You can find information about next month's 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 lecture materials used in the seminar separately?

Please check the lecture materials at the link below!
∙ May Seminar Slides: https://bit.ly/38VZdxG

In this seminar, we are providing Notion lecture notes so you can take notes while listening. Please feel free to duplicate them to your personal Notion or use them on your tablet while watching :)
∙ Notion Lecture Notes: https://bit.ly/3x9ljF5

If you're curious about the live participation reviews,
👏

What was the most impressive content during the seminar?

  • The part where you mentioned that we must consider the audience and the purpose of the report was very impressive! Even though it seems like a basic principle, I feel like it's something I always overlook. Also, the point that the content is more important than the data analysis tools was very insightful!
  • It was great to learn that Google Sheets is used more frequently in the field, as I can keep that in mind when preparing for my job search. Use a hand hoe for what a hand hoe can do..!
  • The lecture was overall very informative! It was also a great help that you pointed out the common mistakes made when writing reports.
  • How to write a report - writing concisely with the content the other party wants!
  • I am currently learning Python as part of the data analysis process, and it's great to learn practical tips like how useful Excel and Google Sheets can be in real-world work.
  • The fact that Google Sheets alone is enough for efficient visualization, and that SQL comes before visualization tools.
  • I was able to learn the differences between reports and dashboards. I also learned what purposes Google Sheets are used for.

A word for Datarian!

  • I am always grateful to Datarian for running these seminars tailored specifically for data analysts every month. I look forward to more great seminars in the future!
  • Through this opportunity, I was reminded of the "goals of analysis" and learned the mindset to streamline my portfolio as cleanly as possible :) I hope to have the chance to meet you professionally after successfully landing a job in the future... I want to meet mentors and bosses like Datarian!
  • I'm currently preparing for a job in data analysis, and because I don't have any seniors in this field around me, I felt lost and worried about whether I could actually do it. However, I feel like those concerns were largely resolved through this lecture! I hope the day comes when I can listen to a lecture as an actual data analyst myself. haha
  • I am growing as I listen every month. Thank you.
  • I liked that the seminar was conducted in a stable manner. Having the lecture notes helped me understand the overall framework before listening, which made the content well-structured. It was also great to get quick answers to my questions in the chat.
  • It was great that you provided lectures and examples based on real-world industry experience! The format wasn't a boring lecture, but rather a continuous communication in a comfortable atmosphere, which was wonderful! I want to keep attending in the future. ㅎㅎ
  • It was great because it was about data analysis stories from the workplace. I want to prepare hard so I can work in the field as well.
  • It was wonderful to be able to learn about the insights and realizations gained by those who have worked in the field for a long time.

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Recommended for
these people

Who is this course right for?

  • I've tried drawing charts with the data, but I'm not sure if I'm doing it right.

  • I need to create a data analyst portfolio, but I'm feeling overwhelmed about how to present the analysis results.

  • I'm curious about how to write a data analysis report that is intuitive and effective for persuasion.

  • What makes a good data visualization? It likely depends on the situation, but I'd like to know the general criteria.

Hello
This is datarian

23,642

Learners

2,768

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/

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Curriculum

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5 lectures ∙ (1hr 17min)

Published: 
Last updated: 

Reviews

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9 reviews

4.2

9 reviews

  • yijuyeon928330님의 프로필 이미지
    yijuyeon928330

    Reviews 5

    ∙

    Average Rating 4.8

    4

    100% enrolled

    It was a helpful lecture. I was able to learn about the parts I was curious about.

    • byeongohahn8213님의 프로필 이미지
      byeongohahn8213

      Reviews 1

      ∙

      Average Rating 5.0

      5

      100% enrolled

      Thanks to you, I learned a lot

      • rlaekdud9229294님의 프로필 이미지
        rlaekdud9229294

        Reviews 3

        ∙

        Average Rating 5.0

        5

        100% enrolled

        • jhpark1029537님의 프로필 이미지
          jhpark1029537

          Reviews 4

          ∙

          Average Rating 4.8

          5

          60% enrolled

          • alsrnrdyd8401님의 프로필 이미지
            alsrnrdyd8401

            Reviews 1

            ∙

            Average Rating 4.0

            4

            100% enrolled

            The content was shallower than I thought ㅠㅠ But it's still good content for reminders!

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