After the comonpletion of the data analysis course, most of the candidates look for a good job, but how they can get it without a strong portfolio? Because job listers will ask for experience and what if it is your first job? Whatever projects you will include in your portfolio showcase your skills to hiring managers. 

Here in this article, we are going to discuss the best data analytics projects for beginners. Even if these projects are not part of your job, you can still show them in your portfolio. So if you are looking to grow your career in this field, you can enroll in the Data Analytics Course in Mumbai. Learning this will help you easily understand these projects.

Which are the Data Analysis Projects?

Here we have mentioned the top five data projects that will help you showcase your skills. This will show that you have completed the Data Analytics Course perfectly.

  1. Web Scraping:

Web scraping is a useful skill for finding and using data from the internet. There are many free public data sets available online, but sometimes they might not cover exactly what you're interested in. By learning web scraping, you can gather data yourself. This shows potential employers that you can find and collect your own data. It also lets you get data that fits your specific interests, even if no one else has put it together.

  1. Data Cleaning:

Cleaning data is a crucial aspect of the responsibilities of a data analyst. Fixing data errors, eliminating duplicates, and filling in missing information are all part of the process. You also need to make sure the data is formatted consistently.

When choosing a data set to practice cleaning, look for one that has multiple files from different sources. These sets usually need more work since they haven't been organized much.

  1. Exploratory Data Analysis:

Conducting Exploratory Data Analysis (EDA) is an essential part of the data analysis process. It's about asking questions and understanding your data better. EDA can be performed either before or after data cleaning.

During EDA, you'll want to:

  • Ask lots of questions about the data.

  • Find out how the data is organized.

  • Look for trends, patterns, and any unusual values.

  • Test ideas and check if your assumptions are correct.

  • Think about what problems the data can help solve.

  1. Sentiment Analysis:

Sentiment analysis is a method used to understand the feelings in text. It helps determine whether the tone of the text is positive, negative, or neutral. Sometimes, it can also identify specific emotions using a list of words linked to certain feelings, called a "lexicon."

Sentiment analysis is especially useful for analyzing reviews and social media posts, where people openly share their opinions on different topics.

  1. Data Visualization:

Humans naturally understand visuals better, which makes data visualization a powerful tool. It turns raw data into clear, engaging stories that can inspire action. Good visualizations aren’t just fun to make—they can also make your portfolio look impressive and professional.

Well, you may need not to spend much amount for this. You can use these five free data visualization tools.

  1. Tableau Public

  2. Google Charts

  3. Datawrapper

  4. D3 (Data-Driven Documents)

  5. RAW Graphs 

Apart from this, there are various other courses such as Power BI Developer Course that can help you to gain the skills. So if you have learned these skills you can be a valuable part of the organization. 

Conclusion:

From the above discussion, it can be said that it is worth investing in learning of the data analytics. Because there is a lot of that there and you can do lots of projects with the same. All you need to understand is where to start from and a proper direction for your next project. Well, you can consider one of these data analysis-guided projects from your peers. If needed you can also take guidance from them for this. So don’t wait long and enroll in the course today.