Data analysis is becoming more and more important in today’s business, where the words AI and machine learning are no longer heard on a daily basis. At the same time, data analysis is often shunned because it is often prejudiced as “complex and esoteric” and “unless you have specialized knowledge.” However, in recent years, various methods for learning such data analysis have been proposed. Here, we will explain how to study data analysis and what you need to do to become a professional human resource.
Table of contents
- The main means of studying data analysis
- Basics of data analysis
- Data analysis skills
- Work that can utilize data analysis
- UMWELT is recommended for data analysis
- summary
The main means of studying data analysis
Data analysis is now an open method for many, and the level of operation is diversifying, so there is more than one way to learn it. You can study at a university, vocational school, book, etc. in a way that suits you.
Go to university / school
The method of studying at university or school gives you specialized knowledge of data analysis. When learning data analysis, three perspectives are important: business engineering and data science. In order to study them comprehensively, it is one of the things to put yourself in an environment where a planned curriculum is prepared throughout the years at the university or school.
Self-taught with specialized books
One way is to learn data analysis on your own through specialized books. This method is excellent in that you can select the learning content according to your interest and understanding, and you can always refer to the framework and code required for data analysis by purchasing a book. You can also study the three perspectives of business engineering and data science comprehensively, or you can focus on what you have chosen.
Utilize learning sites
In recent years, the use of online learning sites has also become a major method. There are free and paid learning sites, and the content varies, so the advantage is that you can choose what you think you need at the moment. The content for beginners is often free, so it is recommended for those who want to learn from the beginning of data analysis.
Basics of data analysis
What exactly should I study when learning data analysis for business use? In the following, we will introduce the ideas and knowledge that are the basis of data analysis.
How to think about data analysis
The key to applying data analysis to your business is to learn how to think about problem solving using data analysis. For example, if you want to increase the sales of a specific product, what kind of problems are expected there, what kind of data can be analyzed to clearly visualize the problems, and how to solve them are assembled in your mind. Let’s be able to. By doing so, you will be able to quickly find a way to analyze the problem at hand. Specific frameworks include logic trees and mathematical formulas.
Basic knowledge and mathematical statistics
Understanding statistics is also essential for data scientists. Statistics can be broadly divided into descriptive statistics (classical statistics), Bayesian statistics, and inference statistics, but at least descriptive statistics should be mastered. The statistical knowledge required depends on the method of data analysis, but if you are independent as an expert, comprehensive knowledge of statistics is an encouraging weapon.
How to use it for business
The purpose of data analysis is to improve your business and solve problems. Let’s formulate and present improvement measures for the issues that have become apparent as a result of data analysis. One of the great advantages of data analysis is that you can visualize the current situation of your company hidden in numerical values. Be aware that you can connect the results to your business by understanding the exact current situation with the right purpose.
Data analysis skills
Once you have a good knowledge of data analysis, you should also improve your skills to actually use it in your business. From here, I will introduce the skills necessary to utilize data analysis in business.
Database Principles and SQL
Skills that understand database principles and SQL and can operate properly are essential for data acquisition. At the stage of collecting the data required for analysis, you need to learn the SQL to operate the database. Also, acquire various skills such as the type of database you use regularly, querying and recoding data.
Languages such as Python and R
Advanced programming skills are not always required, but you must master the programming languages needed for data analysis, such as Python and R. Python has a rich library of statistics, machine learning, data analysis, etc., and is an indispensable language for data scientists. The R language is also used as a data analysis / statistical programming language.
Professional business skills
Specialized business skills are required to apply the knowledge gained from the results of the analysis to the actual business. Machines perform analysis, but humans devise and execute ideas and measures that utilize the results in business. Therefore, skills that can firmly bridge the analysis results and business are required. At the same time, it is also important to have communication skills to convey ideas based on the analysis results to those around you.
Work that can utilize data analysis
There are several types of jobs in which data analysis can be utilized, and they are extremely diverse, including researchers, developers, and engineers. Among them, I will introduce the work specialized in the business use of data analysis.
Data analyst
A data analyst is the job of analyzing the collected data and applying the results to the business. Mostly, it operates data analysis algorithms. There are two main types of data analysts: consulting type and engineer type. If you want to get involved in marketing and sales, you can consult, web media management companies, and ad technology companies. If you want to be involved in development work such as AI development, you often aim for an engineer type.
Data scientist
Data scientists are necessary for the utilization of AI and big data. This person is invaluable because data scientists need not only knowledge of data analysis but also high abilities in statistics and programming. Since it takes time to develop human resources who can play an active role as a force, there is a shortage of data scientists in Japan who can exert their strength as a force immediately.
consultant
As an outside consultant, I also work on behalf of data analysis for various companies. If you do not have the know-how and equipment for data analysis in your company, you can ask an external data analysis consulting service and a specialist called “curator” will perform the data analysis in the latest environment. The merits of requesting data analysis from a consulting service include “the ability to incorporate knowledge from other industries” and “the ability to utilize specialists”.
UMWELT is recommended for data analysis
If you are looking for a tool that can introduce data analysis without specialized knowledge, we recommend the no-code AI cloud UMWELT developed by TRYETING. Since UMWELT comes with a large number of algorithms pre-installed, it is possible to build “any data”, “easy” and “advanced” algorithms by freely combining them. In addition, since there is consulting support after the introduction, it can be useful for in-house training of staff who specialize in data analysis. It has already been introduced in a wide range of industries, from major companies to startups.
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summary
By analyzing and utilizing data, it is expected that information useful for business will be acquired, future predictions will be made, and new businesses that could not be imagined in the past will be created. However, the number of human resources who can utilize data analysis in business is still limited, and it is difficult to train them. If you want to work on data analysis as soon as possible, why not consider TRYETING’s no-code AI cloud “UMWELT”.
