Data analysis language 'SQL'

It's a required competency, not an option.

SQL (Structured Query Language) is a standard language created to manipulate relational databases, and refers to a language for communicating with database systems. In other words, It is a sentence in which the calculation conditions are written in great detail in order to produce the data I want from the place where the data is stored.

비개발직군에서도 SQL 역량을 갖춘 사람을 우대하며 찾고 있습니다.

▶ Even in non-development jobs, we are looking for people with SQL skills with preferential treatment.

If you can handle the SQL language, you can check the data created by our customers by connecting to millions and tens of millions of data management systems at the company. In other words, you can directly identify the characteristics of customers and set and execute specific directions such as marketing promotions, business planning, and strategies.

Therefore, regardless of the job, the ability to use 'SQL', which is the basic language of data analysis Preferential competencies for employment and turnoverIt has no choice but to become.

From a typical liberal arts student,

Right now, I'm Geum Yoon-hye, who is analyzing data.

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Hello, I'm Geum Yoon-hye, a creator who can naturally interpret SQL and help you directly calculate the desired data. I am currently in charge of data analysis in the business innovation team of Delivery App Company B.

Company Y, the first delivery app, used Excel to sort out customer center problems and find ways to improve them. The more you work I realized that in order for my improvements to be applied, I needed to have solid data and logically persuade them. As a result, I felt the need and importance of 'SQL' to be able to access more data.

Learning SQL through books is far from practical. So I started coding line by line so that I could apply it to my work, and now I can extract exactly the data I want. As a result, A typical liberal arts student is in charge of data analysis in the business strategy team of Delivery App Company B.

Data analysis

It starts with an accurate 'data extraction'.

정확한 데이터 추출 → 데이터 분석

▶ Accurate data extraction → data analysis

Why is data-driven decision making a hot topic? Right, based on accurate and diverse data This is because it can create greater financial results. When planning marketing promotions, setting sales goals, or when you need to expand a new business area, the starting point is accurate data extraction.

In other words, I start by defining and extracting the data I want to analyze from a myriad of databases. But if we can't calculate the data ourselves, Make every request to the data manager or data team within the teamI have no choice but to do it.

데이터를 요청하고 기다리는 상황 반복

▶ Repeated situations of requesting and waiting for data

At this time, in order to receive data under the desired conditions, it is necessary to explain in detail via messenger or phone, I just got the results, but it might not be the data you wanted It's there. Or I received the data as requested When analyzing, data is required under another conditionThey also do it. Then the situation of requesting data again and waiting is repeated. Eventually, as this process gets longer, work efficiency and independence are bound to decrease.

If you could generate data yourself, there would be no need to request, explain, and wait for data conditions. It will improve work efficiency, and since I can directly calculate data according to the direction of analysis I think, my work independence can also increase.

I used real SQL

Can I do data analysis?

여러분도 하실 수 있습니다.

▶ Everyone can do it too.

I prepared it meticulously!!!

In the meantime, the students who learned SQL from me were job seekers, marketers, product MDs, sales, and planning practitioners in various jobs. Most of them had never used SQL at all. though Together with me, I learned everything from the basic SQL syntax to the advanced syntax process, step by step, and I was able to accurately calculate the data according to the desired conditions every time I completed the course one by one.

Easy ~ easy ~ from SQL definition

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Theory+ Practices+ Explanatory Solutions, Learn Perfectly in 3 Steps

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The concepts are easy and simple to access, and exercises are prepared for each phrase so that you can apply them. After solving the exercises, I will carefully solve the examples again with me.

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If you are stubborn to the end with me, you can use SQL to directly calculate data and even write your own analysis report.

Using Google Big Query

Practice SQL.

There are various programs that can use SQL, but the SQL course with me uses Google Big Query (Google Big Query) to practice SQL. Even after learning, you can freely review SQL by adding your own data, and learn a wide range of SQL functions.

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You can directly create data tables using Google Big Query (Google Big Query) and Google Sheets, and perform prep and review in the 'SQL Workspace'.

For analyzing marketing promotion results

Let's try to calculate the indicators ourselves?

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If you learn SQL sentence by sentence, it is difficult to immediately use it in practice. So this class “Marketing promotion point payment type event”It is designed so that you can solve the SQL syntax necessary to analyze the performance of as an exercise problem.

Data is like real work how We will proceed with the process of checking one by one whether it is loaded and what is the link between the data.

Changes in sales depending on whether or not an event is in progress
Customer conversion rate by point value range

Design the above event result indicators and write SQL that can directly calculate them.

This class focuses only on “data extraction” so that “SQL beginners & beginners” can use it quickly in practice. Sales planning, marketing, strategy, operations, MD, etc. People in non-development jobs who want to directly calculate data and interpret and use SQL written by othersIt consists only of content for.

Just like analyzing an actual marketing promotion, let's follow the real business process of a businessman and make SQL perfect for you!

Practical SQL for planners/marketers, solid learning from the basics

Practical SQL for planners/marketers, solid learning from the basics