How to make Data Analyst Portfolio?

To begin your career as a Data Analyst, your project portfolio is one of the important thing that helps you to get the job. Why do you need a good portfolio to get the job? Your Portfolio shows skills, experience, expertise and much more.

With the help of this article, I will tell you how I build my portfolio and what things I include in my portfolio.

How to build a good portfolio as a Data Analyst

Your portfolio is the only thing that validates your skills to recruiters. Whatever you mention on your resume your portfolio validates those skill sets.

You need to choose the content of your portfolio. You can make a simple portfolio with at least two sections. In the first section you should talk about yourself and mention your work or projects in second section.

1. About Me
2. Projects

Platforms

Now you need to host your portfolio. Hosting of portfolio is also important. It is not sufficient to mention skills and projects in resume. There are many platforms to host it. few of them are

1. Github
2. Kaggle
3. LinkedIn

What projects you should add to our portfolio as a beginner?

As an aspiring data analyst, you’ll want to demonstrate a few key skills in your portfolio. These data analytics project ideas reflect the tasks often fundamental to many data analyst roles.

1. Web Scraping
2. Data Cleaning
3. Exploratory Data Analysis (EDA)
4. Data Visualisation
5. Sentiment Analysis (A project which uses above all skills)

There’s nothing wrong with populating your portfolio with mini projects highlighting individual skills. But if you’ve scraped the web for your own data, you might also consider using that same data to complete an end-to-end project. To do this, take the data you scraped and apply the main steps of data analysis to it — clean, analyse, and interpret.

This can show a potential employer that you not only have the essential skills of a data analyst, but that you know how they fit together.

There are some projects which you can add in your portfolio from Coursera.

1. Exploratory Data Analysis with Python and Pandas: Apply EDA techniques to any table of data using Python.

2. Twitter Sentiment Analysis Tutorial: Clean thousands of tweets and use them to predict whether a customer is happy or not.

3. COVID19 Data Visualization Using Python: Visualize the global spread of COVID-19 using Python, Plotly, and a real dataset.

Bonus Tip.

Build your portfolio as you learn.

You don’t have to wait for your first job to start developing your portfolio. If you’ve taken classes in data analytics, chances are they included some assignments or course projects. Add those to your portfolio. If you’re learning independently, start completing small portfolio projects as you go. You’ll not only practice your new skills, you’ll have material for your portfolio.