A new career as a data analyst in 5 steps?

Start: Find out if data analytics is right for you

In principle, anyone could become a data analyst. The fact that this option is available does not necessarily mean that you should do it. Certainly don't just start your retraining as a data analyst, but thoroughly investigate whether it suits you before you start this journey.

Answer the questions below for yourself:

• Do you enjoy working together in a team?
• Do you get satisfaction from solving problems?
• Do you find it no problem to regularly work with the highest level of government within an organization?
• Is lifelong learning for you?
• Do you have the motivation and patience to keep working, even if a project gets stuck somewhere?
• Are you a strong communicator?
• Have you always wanted to do something with numbers and statistics?
• Don't you shy away when you hear that learning to program is a must?

Did you answer yes to more than 6 questions? Then there is a very good chance that retraining to become a data analyst is a very good choice for you. Do you want to be 100% sure? Then be sure to read on.
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Step 1. Set aside hours for your data analytics study

Start planning study time. Despite the fact that many people don't like it, good planning can help you study more efficiently and with less stress. Even with a busy life full of obligations, such as pets, chores, and childcare, it's important to schedule flexible study time blocks. Monitor your progress weekly and make adjustments if necessary. Remember: the more time you invest, the faster you can get started as a data analyst.
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Step 2. Learn the data analytics fundamentals

Start with Python, the most popular programming language among data analysts, known for its simplicity, automation capabilities, and powerful libraries like NumPy, Pandas, and Matplotlib. Get to know the basics of Python such as integers, strings, lists, loops, and object-oriented programming. Unsure about these terms? Don't worry! Python is so simple that you'll learn these terms by yourself.

Do you master Python? Then it's time to learn statistics, essential for analyzing and interpreting large data sets. Next, learn how to collect data with CSV files, SQL, and data scraping with Python's Beautiful Soup. Data cleaning with Pandas and NumPy, and data visualization and reporting with Matplotlib and Seaborn are also critical skills.
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Step 3. Dive into the world of machine learning

Do you want your resume to stand out from others? Then it's a good idea to dive into the wonderful world of machine learning. Companies are increasingly using machine learning to gain competitive advantages. That is why more and more companies are looking for people who have this knowledge.
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Step 4. Start creating a portfolio

You need a job to gain experience. But companies will only give you the job when you can show that you have already gained experience. So how can you demonstrate this experience? Well, you do that by entering a portfolio GitHub to build and then also share it on LinkedIn. Using your portfolio, you can show your future employer what skills you have. Do you want to build a good portfolio?

Then make sure you can demonstrate the following:

• That you are creative in your approach to research questions
• What technical skills you have
• How skilled you are at analyzing data
• That you can draw the right conclusions
• That you are good at working with others
• That you can also share your findings with people who have no technical background
• You can work with public datasets

Step 5. Apply for an internship or a job as a junior data analyst

Are you ready for your new job? Then first apply for the position of junior data analyst, this is a great entry position to enter the data science world.

Do you find it difficult to find a job as a junior data analyst right away? Or do you want to take it easy and would like to gain some experience first? Then a traineeship is also a good option. You can often work for the largest and coolest companies or organizations. This gives you a lot of experience and significantly increases your chances of finding a cool job.‍

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Consider getting a degree

Do you want to make sure that your retraining as a data analyst is a success? Then consider the data analytics with Python training to be followed at Winc Academy. You will receive lessons and support from experienced teachers and you will learn how to work with the most important data analyst programs. After completing the course, you not only have a recognized diploma, but also the necessary skills to immediately start working as a junior data analyst.