As the number of companies increases and demands in the field of communication technology increase, the company's need for data analysts is also increasing. If you have a passion for operating numbers, solving problems, and communicating your knowledge to others, pursuing a career as a data analyst might seem like the perfect choice! Previously, you would first need to earn a bachelor's degree in a relevant field. After that, take the time to learn various relevant analytical skills and enrich experience in the field of data analysis. Who knows, in the next few years you will succeed as a professional data analyst!
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Part 1 of 4: Improving Academic Ability
Step 1. Earn a bachelor's degree
Most of the job vacancies for beginners are only for applicants who have completed their undergraduate education and earned a bachelor's degree. To become a data analyst, you generally need to have a bachelor's degree in mathematics, statistics, economics, finance, or computer science.
Step 2. Determine whether or not you need to take the S2 or S3 level
The higher the position of a data analyst, the higher the level of education the applicant needs to have. Generally, a high position is also directly proportional to the amount of salary received, you know! If you are interested in taking a serious career as a data analyst, try evaluating how important an academic degree is to achieving that goal.
For example, you could pursue a master's degree in Data Science or Business Analytics
Step 3. Take a class on a specific subject
If you want to improve your understanding of calculus or programming, consider taking online or offline classes that offer a variety of specific and relevant subjects that a data analyst needs to understand.
If possible, also attend seminars or workshops related to the field held by universities or other local educational institutions
Part 2 of 4: Learning the Required Abilities
Step 1. Master algebra at university level
Every day, data analysts work with hundreds of numbers. Therefore, make sure you have decent math skills. At a minimum, you should master algebra at university level, be able to interpret different functions and graphically represent them, and deal with problems that arise in everyday reality.
Also, make sure you understand the concepts of multivariable calculus and linear algebra
Step 2. Understand statistics
To become an expert data analyst, you must understand statistics to be able to interpret data well. Start by learning basic statistical concepts aimed at high school or university students, then move on to more complex and challenging concepts that are relevant to the job you are applying for.
- The mean, median, mode, and standard deviation are some examples of basic statistical concepts that you likely learned in high school or university.
- Having a solid understanding of descriptive statistics and inferential statistics will also be very helpful.
Step 3. Improve your programming skills
To become a strong data analyst candidate, at least master the basic concepts of programming, and understand some common programming languages such as Python, R, and Java before moving on to more complex concepts and programming languages.
- SQL programming language is also quite popular among data analysts.
- If you want, take various online classes to improve your understanding of data programming.
Step 4. Improve your presentation and communication skills
After analyzing the data, the next step you need to do is to communicate the data to others. Therefore, learn to explain complex information so that it is more easily understood by even very lay people, and learn to use programs that are able to visually illustrate the findings of the data to make it more interesting and easy to understand.
An expert data analyst must be good at communicating data visually and verbally. Therefore, study tools such as ggplot and matplotlib to illustrate the various data you may find
Step 5. Master Microsoft Excel
Because a data analyst must be good at grouping data and calculating numbers, one of the applications that must be mastered is Excel. Don't worry, cyberspace provides hundreds of free video tutorials and websites that can teach you basic Excel concepts.
Step 6. Understand the concept of machine learning
One of the important concepts in the data analysis process is machine learning, which refers to the ability of computers to make predictions or decisions independently after reviewing all available data. To learn the concept, try taking online classes, some of which can even be accessed at no cost.
- To understand these concepts, you need to first master the basic concepts of programming and statistics.
- There are three types of machine learning, namely supervised learning, unsupervised learning, and learning to map situations in order to get maximum results (reinforcement learning).
- An example of supervised learning is the ability of email to filter your inbox and group spam in separate folders. Meanwhile, an example of unsupervised learning is when Netflix recommends a television series or film that suits your tastes, and an example of reinforcement learning is a driverless car that has the ability to observe and adapt to its surroundings.
Part 3 of 4: Seeking Experience
Step 1. Find an industry that needs a data analyst
Focus your search on industries that will most likely require data analysts. For example, marketing firms, technology companies, and financial institutions tend to need data analysts to translate company data and decipher it in easier-to-understand terms.
Search the company's website for the career opportunities they currently offer, or search Google pages if you're not after a specific company. If you have friends or relatives who work in these industries, ask whether or not there are career opportunities that you can try
Step 2. Try an internship as a data analyst
Internship is a very powerful bridge to become a permanent employee in your dream company. Most internship programs are only open to people who have an academic degree (such as a D3 or bachelor's degree). Although it really depends on the industry you choose, you will most likely need to be proficient in a programming language such as Python, R, or SQL. Of course it will be much better if you master all three!
Generally, interns are not paid and are only employed for a few months. Therefore, check all the details listed by the company before applying
Step 3. Join a trade organization
This is a very powerful way to expand opportunities, increase relationships, increase knowledge by attending various seminars, or answering any questions you have regarding the data analyst profession. At the international level, there are organizations that deal with data analysts such as TechAmerica or The Association for Computing Machinery. Search the internet for information about organizations that interest you!
Go to the organization's website, and look for information regarding member registration. Some organizations even provide free membership and give each member full access to upload all available information on their website. But generally, you still need to pay a certain fee to access more premium information
Step 4. Apply for jobs for beginners
Don't be afraid to start your career from the ground up because doing so will enrich you with the knowledge and experience needed to get to a higher position. After all, the salary offered for novice data analysis is already quite large. In addition, most companies are always looking for new people to be placed in the position of Statistical Data Analyst or Business Analyst.
Generally, you only need a bachelor's degree to apply for a job as a novice data analyst
Part 4 of 4: Conducting a Job Interview
Step 1. Create a professional cover letter and curriculum vitae
Remember, these are the first pieces of information about you that companies will see. Therefore, take as much time as possible to put your skills and experience in both, and show that you really deserve the job they offer. Make sure you also take the time to edit both before sending them to the targeted company.
Step 2. Research the company you are applying for before the interview
Doing so can increase your readiness for a serious job discussion with the interviewer. Therefore, try visiting the company's website to find out all the projects they work on and/or the programs they use.
If the company you're applying to has a social media account, follow their account for the latest updates they upload
Step 3. Practice answering the various questions that may be asked
Browse the internet to find examples of questions that might be asked during an interview. After that, simulate your answers in front of those closest to you, or try recording your answers and evaluating them.
Some of the commonly asked questions are, “What do you think is the definition of big data?” or “What problems do you think analysts commonly face when analyzing data?”
Step 4. Get ready to present your technical skills
While this will depend heavily on the job you are applying for, you will likely be asked to demonstrate technical skills relevant to the job. Therefore, take the time to find out the types of programs used by the company before conducting the interview process, and be prepared to present your abilities in using these programs.
Some examples of technical skills that generally need to be demonstrated are coding skills (translating logic into programming languages), programming, or analyzing data using various resources
Step 5. Ask the interviewer questions
At the end of the interview process, ask questions like, “What kind of project would I be most likely to work on?” or “What program does the company use to create data visualizations?” Doing so will further confirm your interest in the job, as well as make you a better candidate. easy to remember.
