We will explain the demand for data analysts in companies, the skills that can be used, and the future prospects. These jobs fall under the data scientist job category, which is gaining attention in recent years. Data analysts are professionals who specialize in data processing and current situation analysis, and are good at advanced mathematical processing. Is it possible for a data analyst to work independently as a freelancer?
- Average Annual Salary for Data Analysts
- The difference between a data analyst and a data scientist
- Demand for data analysts
- Qualifications that help data analysts
- Data analyst career path
Average Annual Salary for Data Analysts
If a data analyst is a company employee, the annual income is often around 5 million to 6 million yen. As for what happens when this becomes a freelance, many data analyst projects are around 500,000 to 800,000 jobs, and by simple calculation, it is possible to aim for close to 6 million to 10 million. But the answer is that it depends on the person, as it all comes down to skill. Whether or not you can get a high-paying job as a data analyst will depend on whether or not you have the following essential skills.
Basic knowledge of mathematics and statistics
All data scientist positions require academic ability. To build a career and succeed as a data analyst, you need basic university level mathematics knowledge. It is necessary to focus on acquiring knowledge of statistics, which is the basis of data analysis. If you don’t have this knowledge, you won’t be able to handle your work. For this reason, companies often require a degree in statistics, so if you have no experience, it is best to aim for a science-oriented university. As you gain experience, you will be able to solve clients’ problems like a consultant.
As a data analyst, you will be responsible for collecting and viewing vast amounts of data within databases. Skills and understanding of operating databases and SQL in a practical environment are also required. Of course, specific tools such as Oracle, SQL Server, and BI tools can be used for free on the web, so it is highly desirable to be able to do so. Once you acquire advanced technical skills, you will be able to implement measures to solve problems, make predictions, and propose services within your own company. Learn to specialize.
It sometimes do simple programming by hand based on data analysis. Python is the main language, but it is also a good idea to have sufficient knowledge of analysis tools such as SAS and R. Furthermore, if you become familiar with public clouds such as AWS, you will be able to expand your range of activities as an expert in the latest systems and marketing business, and expand your possibilities and make improvements. Hiring is also increasing because there is a shortage of manpower in fields where needs are increasing. Let’s make it operational by doing simple aggregation and getting involved.
The difference between a data analyst and a data scientist
A lot of people confuse data analysts with data scientists. It can’t be helped either. This is because the world of data science has only recently begun to attract attention. A data scientist refers to a job that analyzes big data and provides consulting for problem solving, or a general job that has the aspects of a data analyst or machine learning engineer. Refers to an engineer who specializes in
Demand for data analysts
Not only data analysts, but data science jobs in general are still not so well known. Against this background, there are clearly fewer freelance jobs for data analysts than for system developers and infrastructure engineers. Even if you’re a seasoned analyst, you don’t have a lot of work to do, so it’s a good idea to first sign up with an agent as much as possible. Since the amount of work is small, there are few competitors, so if you can find a job, you can get a job quickly.
Qualifications that help data analysts
There are no required qualifications to be a data analyst, but having the following qualifications will make it easier to get work orders. Although it is a niche field when looking for a job, there is high demand in certain fields. By doing these things, you will be able to present solutions to problems you are facing, and you will be able to make full use of statistical methods and models, which will bring you great benefits. You will be able to work in deeper areas. Since there is a serious shortage of human resources, the person in charge will be primarily a marketer.
Graduated from a science university
A college degree in mathematics or statistics is highly valued. It is interpreted as having basic knowledge in statistics. It is highly recommended because it is very advantageous not only for freelance but also for getting a job just by having this. The tuition fee is higher than the liberal arts course.
The Statistical Test is a nationwide standardized test that evaluates the knowledge and utilization of statistics. It consists of 5 levels from 4th grade to 1st grade. The knowledge that can be obtained in statistics is essential for data analysis, so it is worth acquiring it.
Database knowledge is very important in data science work. It is a qualification that proves management skills of Oracle Database, which boasts the No. 1 share as a commercial database, so it is advantageous to keep it. Starting with Bronze, there are four levels of qualification, from Silver to Gold to Platinum.
Python3 Engineer Certified Data Analysis Exam
The Python3 Engineer Certification Data Analytics exam is also important. Python is also a language that most data scientists can handle, and is in considerable demand in the commercial world. In addition to basic syntax, knowledge frequently used in actual development work such as “data analysis” and “mathematics” will be tested.
Data analyst career path
Career paths for a data analyst include: A wide variety of career paths are available as experts, such as problem-solving consultants who formulate hypotheses through appropriate study and acquisition and know-how, data mining, artificial intelligence, system efficiency implementation, and automation support. there is. There are also careers as advisors and project presentations.
The pattern is for them to continue handling statistical tests on a daily basis, playing the role of a basic and upstream data analyst, and gaining an excellent track record in their work as a person in charge. This is a plan that allows you to grow by continuing to refine your professional skills. As a specialist in current situation analysis, in addition to design skills such as defining the purpose of analysis and selecting analysis methods, I also have the perspective to grasp the obtained results and use them to improve sales and make decisions for a business. Is required. As you advance in your career, your market value will also increase.
There is a transition to a management position leading a data analysis team. My career plan is to further improve my communication skills, strategy formulation skills, and negotiation skills with customers and users. If you are interested, you can greatly increase your value by becoming familiar with it, so we recommend that you stay involved in the organization. We need to be sensitive to technological innovations as technology continues to evolve, deploy, and verify alternative technologies.
Changing jobs in different industries
In the end, there is a way to transfer to a different field. If you are a data analyst, you can become a data scientist. There are also career plans for data engineers and machine learning engineers, so there are many options. If you change your learning policy or tendency, you can also pursue other different careers such as learning the new R language, in-house system engineering, or consulting. There are job openings available, and there is a shortage of human resources, so there are opportunities.