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BigQuery(SQL) Application (Funnel Analysis, Retention Analysis)

We conduct app log analysis using data from Google Analytics 4 and Firebase. It includes useful content for practical use, such as arrays, window functions, funnels, retention, Google Sheets, and more.

(5.0) 51 reviews

512 learners

  • kyleschool
데이터분석
bigquery
데이터시각화
SQL
Firebase
Google Sheets
Google Analytics

Reviews from Early Learners

What you will learn!

  • BigQuery

  • SQL

  • Google Sheets

  • Window function

  • Handling ARRAY, STRUCT (UNNEST)

  • App Log Data Analysis

  • Retention analysis

  • Funnel analysis

How to do funnel analysis/retention analysis using data from Google Analytics 4 and Firebase?

When I was a new employee, I first encountered Google Analytics and Firebase data. At that time, there was almost no data on user log data, and I had no idea how to handle this data. While looking at various materials, I learned how to load user log data generated from GA4/Firebase into BigQuery and how to analyze the loaded data. As I accumulated more and more experience, I have now created my own pattern. I would like to share the contents.

In the BigQuery utilization section, you will learn functions that were not covered in the BigQuery (SQL) introduction for beginners while conducting funnel analysis and retention analysis. The difficult parts when approaching BigQuery are ARRAY and STRUCT, and I will share how to approach these parts. After that, I will introduce window functions. If you learn window functions well from the beginning, it will be very convenient when writing SQL in the future. I will introduce window functions based on cases that I have experienced in the field.

🎈 Recommended for those who use Google Analytics 4 and Firebase 🎈

Google Analytics 4 and Firebase have retention features, but they are difficult to use in practice due to functional limitations.

  • Limitations of functionality: It is difficult to sample data and set detailed conditions on retention.

For this reason, you need to export data to BigQuery and write retention yourself. If you are in that situation, you can apply it right away by taking this course. It covers in detail what criteria to use to write retention and how to interpret it.

🚀 Also recommended for those preparing for SQL coding tests 🚀

You can solve the basic part of SQL coding test by looking at the introduction, and in-depth content of SQL coding test often comes up with problems that extract data by giving window functions or specific logic. It is possible to solve these problems many times, but it requires a process of thinking about difficult logic yourself.

The lecture is designed so that you can solve it by presenting various practice problems in the lecture. You can get a feel for the ARRAY and window function parts by solving practice problems. Most of the problems in the window function are given with similar patterns (only the data is different). You can look at these problems and think about how to solve them.

In the retention part or custom session creation part, you specify specific logic and write that part as a query. Think about the input of the data and the final desired output form, and write the query while thinking about the intermediate output of the process . This part may feel difficult at first, but it's okay. This lecture is a lecture to maximize your ability, so it's natural to feel that way at first (I did too). However, if you take the lecture well, I think your SQL ability will improve a lot.


There is a student who took the course up to the utilization level and left comments about the coding test. He said that he passed the coding test of a domestic unicorn company that we all know.

🎁 I recommend it to those who have used BigQuery quite a bit or those who use other DBs 🎁

We thought about how to make it so that even people who have been using BigQuery for more than 3-4 years can get help, and included the contents.

Even if your company doesn't necessarily use BigQuery (even if you use Spark or another DW), you will still get something out of this course. The flow of writing queries, what problems are you writing queries to solve, and how should you think? This part will be helpful to you.


We are sharing reviews left by our students.


I'm sharing some of the reviews left by other students (you can read more about them in the article below)

What if someone with 5 years of SQL experience takes a BigQuery course?

Questions to determine if you should take this course


Please look at the two questions below and think about whether the correct answer is obvious.
The first problem is to think specifically about what action to take , and the goal is to present specific action items rather than simply ending with one or two lines.
The second problem is the problem of handling NULL in the Windows function ( Windows function practice problem: You need to give a specific option, not just the LAG function, to get a normal value)

Interpreting the Weekly Retention Curve from Lectures: How to Interpret It?

Windows Function Practice Problem: It needs to be run with specific options, not just the LAG function

If you don't have an immediate answer to the question above, I recommend taking this course.

Features of this course

📌 I created the app log data myself. It is about 700,000 rows, and I created the app data for the delivery service.

📌 We share BigQuery advanced grammar (ARRAY, STRUCT, UNNEST, window functions, DECLARE, etc.) and how and when to use it . We only include the content that is absolutely necessary in practice.

📌 I will share with you how to interpret funnel analysis/retention analysis , not just writing queries and ending. When I was a junior, it was really difficult to just write queries and think about what to do at the company. I will share my experience in this area.

📌 We will share a simple visualization method using Google Sheets , and also share useful content that can be used in practice, such as schedule queries and VIEWs.

📌 There are practice problems and assignments . For the parts where you need to get used to grammar, we provide practice problems (ARRAY: 4 problems, PIVOT: 3 problems, Window function: 9 problems), and for the retention analysis and overall assignments, we provide assignments based on tasks that you can experience in the field. If you solve these parts and post them on the bulletin board, we will give you feedback.

📌 This lecture is not for beginners. It is for those who have taken the BigQuery (SQL) introductory course for beginners or know about SQL JOIN.


I recommend this to these people

Anyone who needs to analyze app logs
Those who want to analyze app logs and derive action items rather than simply writing queries

For those who need in-depth learning of BigQuery
Anyone who uses BigQuery at work and needs more in-depth learning

People in the Product Analyst position
If you are a product analyst, you are curious about funnel analysis and retention analysis, which you must experience.

After class

  • You will be able to use BigQuery to do funnel analysis . As you think about what parts are important in funnel analysis, you will also be able to write queries for the funnel.

  • You will be able to use BigQuery window functions . You can become familiar with the different types of window functions and when to use them by solving practice problems.

  • You can handle ARRAY and STRUCT in BigQuery.

  • You can now do PIVOT in BigQuery

  • You will learn how to conduct retention analysis and how to write queries.

  • You can save and use UDF.

  • Understand how to leverage log data from Google Analytics 4 and Firebase

  • You can export and visualize data from BigQuery using Google Sheets .


🔥 After class, coaching event 🔥

After you have taken more than 75% of the lecture, if you leave a survey, we will conduct coaching. The coaching topic will be based on the assignment in the BigQuery utilization section, and we will provide detailed feedback on how to write it better. Or, you can just talk lightly about this assignment and talk about your personal concerns.

For more details, please refer to lectures 0-5.

Who created this course

  • Cloud GDE (Google Developer Expert)

  • Google BigQuery Complete Guide Translator

  • Boostcamp AI Tech Instructor - Product Serving/Learning Master (2022 ~ Present)

  • Kyle School (July 2022 ~ Present): Data Coaching, Consulting (DA/DS/DE), Education

  • Socar Data Scientist (2018.09 ~ 2022.07)

  • Retrica Data Analyst & Data Engineer (2017.02 ~ 2018.04)

  • Tech Blog: https://zzsza.github.io/

  • YouTube: Kyle School

  • Instagram: @data.scientist

Learn about these things.

Big Flow Diagram of Funnel Analysis

Big Flow Diagram of Retention Analysis


Summary of Windows Function Core


Handling Array Data: Flattening with UNNEST


Things to note before taking the class

Practice environment

Learning Materials

  • It is provided in PDF format, and we also run a Discord channel, so feel free to ask questions if you have any.

Player Knowledge and Notes

  • You should take the introductory course on BigQuery (SQL) for beginners to understand it smoothly.

  • However, for those who did not take the course, I will summarize the lecture and mention only the necessary parts so that you can take the course in part.

  • If you want to leave a lecture record on your blog, you can do so by leaving the lecture URL. However, sharing the data or PDF file itself is not possible.

    • However, uploading most of the lecture may cause copyright issues. I recommend that you write an article by adding your own thoughts and the key points you want to remember from the lecture.

    • If you look at the blog posts, you can think about it from the perspective of whether it is okay to not take the class.

Recommended for
these people

Who is this course right for?

  • For those who have learned the Introduction to BigQuery (SQL) for beginners and wish for additional learning

  • Data analysts looking to improve SQL skills

  • Product Analysts: Funnel/Retention Analysis in BigQuery required.

  • For those who want to learn BigQuery array data, window functions

Need to know before starting?

  • BigQuery(SQL) Lecture for Beginners

  • Basic SQL syntax must be known (SELECT, FROM)

Hello
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9년차 데이터 과학자, 데이터 엔지니어, 머신러닝 엔지니어로 근무했으며, 쏘카와 타다에서 데이터 분석, 데이터 엔지니어링 개발, 머신러닝 알고리즘을 개발했습니다.

카일스쿨 유튜브에 데이터 커리어 관련 영상을 올리고 있으며, 어떻게 해야 강의를 수강하신 분들이 회사에서 일을 잘할 수 있을까?를 고민하며 자료를 만들고 있어요.

Google의 GDE(Cloud)로 활동하고 있어요.

 

카일스쿨 유튜브 : https://www.youtube.com/c/kyleschool
기술 블로그 : https://zzsza.github.io/
인스타그램 : https://www.instagram.com/data.scientist/
대표 컨텐츠 : https://github.com/Team-Neighborhood/I-want-to-study-Data-Science
데이터 과학자가 되기 위해 진행한 다양한 노력들 : https://zzsza.github.io/diary/2019/04/05/how-to-study-datascience/

Curriculum

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62 lectures ∙ (10hr 35min)

Course Materials:

Lecture resources
Published: 
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Reviews

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51 reviews

5.0

51 reviews

  • homebrew1님의 프로필 이미지
    homebrew1

    Reviews 2

    Average Rating 5.0

    5

    79% enrolled

    기본 강의 완강 했던 학생입니다. - 내용은 크게 1. BIGQUERY 심화 문법 2. PM 적인 사고법 입니다. - 1은 제가 원래 바라고 있던 내용이라 만족감이 정말 컸습니다. 아마 GA4로 데이터 분석 하실 마케터분들이면 무조건 알아야 할 내용 이라고 생각합니다. - 2는 제가 이미 알고 있던 내용들이 었지만, 실제 회사에 다녀보시지 않았거나 하신분들은 필수로 알아야할 내용이라, 그로스 해킹 / 리텐션 등의 용어에 익숙하지 않으신 분들에겐 유용하다고 생각이 들었습니다. - 강의 외적으로, 디스코드도 파시고, 피드백도 계속 모니터링 하시고, 1:1 코칭까지 해주시는것이 가장 인상 깊었습니다. 강의 금액을 떠나서 수강생들에게 신경 써주시려고 하시는게 느껴집니다.

    • 카일스쿨
      Instructor

      homebrew1님 안녕하세요! 기본편, 활용편 수강해주셔서 감사합니다. 강의를 수강하시면서 해소가 안되는 부분이 있다면 제가 꼭 도와드리고 싶은 마음에 1:1 코칭, 디스코드를 운영하고 있어요. 문제를 같이 해결하고, 실질적으로 도움이 되는 교육을 계속 만들어볼게요. 감사합니다!

  • 흰임금펭귄님의 프로필 이미지
    흰임금펭귄

    Reviews 1

    Average Rating 5.0

    5

    32% enrolled

    *𝓑𝓮𝓼𝓽 𝓢𝓠𝓛 𝓒𝓸𝓾𝓻𝓼𝓮 𝓸𝓷 𝓘𝓷𝓯𝓵𝓮𝓪𝓻𝓷 𝓲𝓷 2024* 기초편 수강평 보신분들은 아시겠지만 정말정말 sql 활용자에게 좋은 강의입니다🥺ྀི 개인적으로 인프런 넘버완~ 가격이 두배여도 들을 강의 분석가가 아닌 포지션에서 남이 짜둔 SQL을 여차저차 활용하며 야생쿼리로 성장하신 분들 으레 있지않으실까요? 그랬던 과거의 저에게 강의 하나만을 추천한다면 바로 카일스쿨... 본인의 회사에서 빅쿼리를 활용한다! (빅쿼리 활용법까지 상세히 알려주십니다) 다 짜놓은 쿼리에서 조건만 조금 수정해서 돌릴 수는 있는데 혼자 짜라면 못짜겠다! 어떻게 짜긴 짜는데 이게 어떻게 정제과정을 거치는지 모르겠다! 기다렸습니다 제대로 모시겠습니다 바로 구매GO🏃🏃 그럼 다음편이 나올때까지 숨 참으러 이만(흡~)

    • 카일스쿨
      Instructor

      우와 너무 감동적인 수강평이네요. 회사에서 인수인계 받은 쿼리를 뜯어보면서 저도 참 어려움을 느꼈던 시기가 있었어요. 이 부분을 많은 분들이 덜 겪었으면 좋겠다고 생각했어요. 수강해주셔서 너무 감사합니다!!

  • 레오나님의 프로필 이미지
    레오나

    Reviews 5

    Average Rating 5.0

    5

    100% enrolled

    카일님 덕분에 국내 유니콘 기업 SQL테스트, 직무인터뷰 합격했습니다! 경력직이지만 코테가 처음이라 오히려 긴장을 많이 했는데, 너무 수월하게 풀었어요. "어렵게 내면 나온다"고 하셨던 리텐션 문제가 진짜 나왔고ㅋㅋ 강의에서 많이 다뤘던 로직 덕분에 오히려 가장 쉽게 풀었습니다! 솔직히 '듣기만 하면 누구나 합격보장'은 아닌거 같구요. 저는 스터디 참여해서 문제 열심히 풀고, 강의 커뮤니티에서 다른 분들 풀이도 분석하고, 만들어주신 데이터셋으로 문제 직접 만들어서 풀고... 최대한 배운대로 해보려고 노력도 많이 했습니다. <강의 뽕뽑는 팁> 하수: 강의를 듣기만 한다 중수: 과제 스스로 풀고, 연습한다 고수: 커뮤니티 활용, 1:1코칭도 아끼지 말고 꼭 받는다 (+ 1:1로 조언 많이 얻었고 직무인터뷰까지 합격했어요🤙) 그리고 인프런 로드맵 기능 모르는 분들이 많은데, 참고해보세요. https://www.inflearn.com/roadmaps/4639 몇 년 전 블로그부터 이번 강의까지 직간접 도움 많이 받았는데 리뷰는 처음 남기네요. 첫 신입 취준부터, 업무에서도, 이직할 때도, 제 회사 밖 사수가 되어주셔서 감사합니다🙏 마지막에 예고하신 다음 강의도 기다리고 있겠습니다!!!

    • 망고맛있어님의 프로필 이미지
      망고맛있어

      Reviews 18

      Average Rating 5.0

      5

      100% enrolled

      빠짝스터디 참여로 본 강의를 수강 하게 되었습니다💪 스터디로 몇 주 만에 강의를 완강할 수 있었네요:) [수강평] 1. 실무 중심적인 데이터 분석을 경험해 볼 수 있다 : 기존 강의들에서 잘 알려주지 않는 BigQuery를 이용한 데이터 분석을 중점으로 가르쳐 주십니다. 많이 사용하지만, 여느 강의에서도 잘 나와 있지 않는 리텐션(retention), 퍼널널(funnel)분석, 코호트 분석에 대하여 배우실 수 있습니다. 이 강의야 말로 현업에서 BigQuery를 사용하는 방식, 실무를 경험할 수 있는 강의하고 생각합니다. 2. 경험이 많은 강의자와의 원활한 소통 디스코드방도 운영하고 계시고, 강의의 커뮤니티 > 질문을 통해 소통할 수 있다는 것이 또 다른 장점이었습니다. 다른 강의에 비해 수강자의 의견과 질문을 잘 들어주시려 노력한다는 것이 느껴졌고, 데이터 분석 경험자의 조언을 들을 수 있어 좋았습니다. 특히, 수강 완료시, 1회 고민상담권?을 얻을 수 있다니 멘토를 얻은 기분입니다. 3. 어려운 문법도 쉽게! : 개인적으로 윈도우 함수를 독학하는 것이 힘들었는데, 쉽게 알려주시고, 실제 로그 데이터에서 어떻게 사용되는 지 알 수 있어 좋았습니다. 또한, 현업에서 많이 사용되는 unnest, array의 사용법 및 활용법에 대하여 배울 수 있어 좋았습니다. 4. 현업과 유사한 데이터에 배운 내용을 적용해 볼 수 있다! : 배운 내용을 실제 데이터에 적용하는 게 어려울 때가 많은데, 어떤 기술 이나 문법을 배울 때 마다 현업 데이터와 비슷한 log 데이터에 배운 내용을 적용해보는 커리큘럼이 있어 좋았습니다. [추천대상자] 1. sql 기반 데이터 분석을 경험하고자 하시는 분 2. 실무기반 데이터 분석을 경험하고 싶으신 분 3. 데이터 분석가 꿈꾸미 및 이직 준비 중이신 분

      • 카일스쿨
        Instructor

        망고맛있어님 입문편에 이어 활용편에도 자세한 수강평 남겨주셔서 감사합니다. 이번 경험을 통해 망고맛있어님이 발전하셨을거에요. 앞으로도 계속 발전하시길 바랄게요! 코칭권은 고민이 있을 때 찾아주셔요..!

    • 박재은님의 프로필 이미지
      박재은

      Reviews 3

      Average Rating 5.0

      5

      100% enrolled

      작은 규모의 스타트업이라 데이터 분석가가 없어 PM이 직접 쿼리로 추출하는 업무가 자주 있는데, 리텐션과 퍼널 분석 등은 쿼리가 복잡해 시도를 하지 못했는데요. 마침 빅쿼리 활용편으로 강의명에 똭 원하던 내용이 나와서 고민 안하고 수강했습니다! 이미 어느정도 SELECT, JOIN 은 능숙하게 하시는 분들이시라면 충분히 따라잡기 쉬울 것 같고요 만약 SQL이 처음이다 하시면 기초를 수강하신 후에 활용편을 듣는 것을 추천드립니다. 여기서 배운 윈도우 함수는 실무에서도 바로 써먹을 정도로 유익했습니다. 리텐션분석과 퍼널분석도 차근히 해보겠습니다. 좋은 강의 열어주셔서 감사합니다 :)

      • 카일스쿨
        Instructor

        재은님 수강평 감사합니다. 3개월이 지났네요. 배우신 내용 잘 활용하고 계실지 궁금하네요. 앞으로도 계속 발전하시길 바랄게요!!

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