Skills You’ll Learn
Creating an environment that utilizes data
Learn why data utilization environments are important and how to create them
Analytical work in various environments
Learn what data analysis tasks should be done in various environments
Basic data analysis skills
Learn what basic competencies you need to have before analyzing data
Class introduction
If you want to grow your business through data analysis, you need to create a good environment for utilizing data. Therefore, this class does not teach how to analyze data. We will talk about 1) what “analyzing data” means in business, 2) how to create an environment that utilizes data, and 3) what value can be extracted from data from various environments.
If you are a data analyst, PM, or marketer who is analyzing data but is worried about whether it is contributing to business growth, you will be able to get clear answers in this class.Kwh
▶ Data usage components
▶ Why you need to create a data strategy & roadmap
Course effect
- You can learn what an environment is good for using data and how to create such an environment.
- Data analysis work also varies depending on who and what kind of work you do. 1) When you collaborate with executives/PMs/data engineers, 2) you learn the scope of work and roles according to the growth stage of the business.
- You can have the necessary competencies to do a good job in data analysis, such as an understanding of the organization, services, and data, and a framework for KPIs.
Recommended target
- Junior PMs, marketers, and data analysts who want to know what kind of data they need to analyze and why it's not doing well
- People who want to create a company, culture, or environment that makes decisions based on data
- Those who want to develop the necessary competencies to become data analysts leading business growth
Two things make this class special
❶ No one told me
Redefining the core business of data analysis
Does dealing with analysis tools such as Python, SQL, and R mean data analysis?
It's not. The core task of data analysis begins with setting goals. Set goals for data analysis that are the same as the direction of the business, and learn how to have an environment where data can be collected and analyzed well to achieve them. Finally, for effective analysis, we learn analytical methods that are meaningful to the business by continuously experimenting and asking questions.
❷ Creating business growth
A Data Analyst's Perspective
An 'understanding of the world' that can utilize data is essential for organizational growth. In other words, 1) data analysis cannot be performed without knowing the 'three elements of the organization', and 2) Data analysis without considering the 'three elements of service' is meaningless. 3) It is designed so that everyone who has taken the class can have the perspective of a data analyst who creates business growth by properly understanding the 'three perspectives of looking at data'.
Curriculum
Creator
Summer Rain
I originally studied economics, but when the AlphaGo craze hit, I became a data analyst with the idea of analyzing data to better understand the world.
In an ordinary company other than a unicorn, I learned planning, learned data engineering, learned mathematics, and gained experience by rolling, rolling, shoveling, and shoveling to find my own answers in order to analyze unusual data.
As a result, I began to look at using data from various perspectives, and I wanted to share it with others. So I wrote a post for brunch under the name Summer Rain and posted content on LinkedIn to sort out my thoughts.
Thankfully, many people sympathized with my article, but I finally came up with a lecture proposal from Class101 and I was able to create a course
I hope that many people will learn more about data through my lectures (not just plain language machine learning and Python!)
여름비 브런치
