As companies expand and multiply, the demand for data analysts has never been higher. If you love numbers, solving problems and communicating your knowledge to other people, this career may be the perfect choice for you. Get a college degree, learn the necessary analytical skills, gain work experience, and you'll be well on your way to becoming a successful analyst.
Steps
Part 1 of 4: Improve Your Education
Step 1. Get a degree
Almost all first-level jobs for analysts require at least a three-year degree. To become an analyst, you must major in math, statistics, economics, marketing, finance, or computer science.
Step 2. Decide whether to pursue a master's degree, a master's degree or a doctorate
Senior analyst jobs may require these degrees and usually guarantee a higher salary. If you are interested in this industry, think about which titles may be most useful for you and your career.
Examples of high-level degrees are Masters in Data Science or Business Analytics
Step 3. Sign up for courses that cover specific topics
If you think you need help with algebra or want to learn programming, sign up for a course that teaches you the skills needed to become an analyst. You can follow them in person or via the internet.
When looking for courses, check if the local university offers seminars or courses in the subject you are interested in. You can also participate in workshops in your area
Part 2 of 4: Learning the Necessary Skills
Step 1. Master college-level algebra
Analysts work with numbers every day, so make sure you're comfortable with math. It is important to understand algebra well; you should know how to interpret and graph various functions as well as knowing how to solve real problems.
It will also be useful to know multivariable calculus and linear algebra
Step 2. Know the statistics
To become a data analyst, you need to be able to interpret information and this is where statistics come into play. Start with the high school or college level basics, then move on to the more advanced information required for your specific job.
- Mean, median, fashion, and standard deviation are some examples of the statistical concepts you would learn in high school or college.
- It will be useful to be familiar with descriptive and inferential statistics.
Step 3. Improve your programming skills to become a more interesting candidate
While you don't need to be a programming expert to start working as an analyst, you should at least know the basics of languages. Start by learning to use languages like Python, R and Java, then move on to the others.
- SQL programming is a common requirement for data analysts.
- You can take courses on the internet to learn programming.
Step 4. Develop excellent communication and presentation skills
Once you have analyzed the data at your disposal, you will need to talk about it with other people. Learn to explain complex information so that non-analysts understand it and practice using programs that allow you to visually present data clearly.
You should be able to communicate data visually and verbally. Learn to use tools like ggplot and matplotlib to present your findings
Step 5. Learn to use Microsoft Excel
As an analyst, you will need to organize data and do calculations, so you need to be able to use Excel perfectly. You will find many videos on the internet, as well as free websites, which will help you to exploit the full potential of this program.
Step 6. Learn machine learning
This technique, that is, teaching a computer to make predictions and make decisions on its own once it has analyzed the data, is important for data analysis. Search the internet for courses that can teach you everything you need to know about machine learning; you will even find some free ones.
- To understand machine learning, you need to have a foundation in programming and statistics.
- There are three types of machine learning: supervised learning, unsupervised learning, and reinforcement learning.
- An example of supervised learning is the e-mail program that filters incoming messages and puts spam in a specific folder. Unsupervised learning is what allows Netflix to suggest TV shows and movies you may like, while an example of reinforcement learning is a self-driving car that has the ability to "see" and adapt to its surroundings..
Part 3 of 4: Gaining Work Experience
Step 1. Look for companies that need data analysts
Focus your research on the areas where the demand for analysts is greatest. Marketing firms, technology firms, and financial institutions have a tendency to hire analysts who are able to interpret data and explain it in an understandable way.
Visit the websites of the companies you are interested in and search for vacancies, or do a general internet search. If you already know someone who works in one of those industries, ask them if they know any companies they hire
Step 2. Apply for an internship as an analyst
Internships are the ideal way to make your first entry into a large company. To participate in many internships, you will need to be enrolled at the university. Depending on the industry, you will need to know Python, R or SQL; if you want to be more confident, learn all three.
Many of these internships are unpaid or last a few months, so check before applying so you know all the details
Step 3. Join a commercial organization
These entities allow you to leverage resources such as workshops, networking opportunities, or online help centers. There are several related to data analysis. Do some research on the internet and find one that interests you.
To join a commercial organization, visit the institution's website and find the required procedure. You may sign up for free and have access to a limited number of resources. There are usually various types of participation, which offer different privileges based on the quota
Step 4. Try to get low-level jobs
These professional positions allow you to learn and gain experience that you will need for higher-level analyst jobs. You will still have a great salary and companies are always looking for staff for the roles of Statistical Data Analyst or Business Analyst.
Low-level jobs usually require a bachelor's degree, not a master's or doctorate
Part 4 of 4: Taking the Job Interview
Step 1. Write a professional resume and cover letter
These documents are your business card for your potential employer. Spend some time describing your skills and work experience to show that you are the right person for the job. Once you're done, be sure to reread it carefully, so that all mistakes are corrected.
Step 2. Research the company before the interview
This way you will show up prepared to have a real conversation about employment. Go to the company's website and find out about the projects they work on and the programs they use.
If the company has social media profiles, read the latest updates that have been posted
Step 3. Practice answering potential questions
Search the internet for questions that may be asked. Practice with the answers in front of a friend, or sign up and try to improve.
Some possible questions are "How would you define big data?" or "Tell me about the most common problems analysts encounter during analysis."
Step 4. Get ready to show off your technical skills
Depending on the job, you may be asked to demonstrate your skill. Find out what kind of programs the company uses before the interview and be prepared to show that you are able to use them perfectly.
Technical skills required include knowing how to program or analyze data using various sources
Step 5. Think about the questions for the examiner
At the end of the interview, ask questions like "What kind of projects will I be assigned?" or "What kind of programs do you prefer to use for data visualization?". By asking questions you will show that you are interested in the job and will remain more impressed in the examiner's mind.
