Data analysis will provide an excellent professional start, but every potential employer must be aware of your initiatives. A future data analyst must have experience in a variety of fields and develop their skill to transfer into the next big data analyst project idea.


Businesses are looking for data analysts familiar with the problems facing a specific industry and can list their past initiatives. Projects can be complex, especially if your data analytics portfolio is new to you. The most important thing is to demonstrate your skills with a relevant dataset. The fact that data is available everywhere is excellent news; you just need to know where to look for it.

Data Analytics Portfolio

In your portfolio, you must show that it is possible to carry out numerous sorts of data analysis. It must also demonstrate your ability to compile, concisely, and visually present your results. The portfolio is getting more sophisticated as people get greater capabilities.

Data Analytics Project Ideas

Here are six project suggestions that can assist you in starting from scratch to create your portfolio in the fields of data scraping, exploratory analysis, and data visualization.

  • Data/web scraping project Ideas:


Web scraping goes under many names, including screen scraping, web harvesting, and others. It is a method used to gather a sizable amount of data from websites and store it somewhere. Software like Parsehub, ScraperAPI, Octoparse, and libraries like Beautiful Soup or Scrapy may automate the web scraping process. Whatever approach you use, it’s critical to show effectiveness. Trainers at IBM-accredited data science course in Chennai can guide you through various data science and analytics projects. 


  1. Job portals: 

Due to the prevalence of standard data forms on job portals, many new hires like scraping information from them. You may also find a tonne of operating demonstration videos online. Why not focus on your industry and keep it engaging? Gather information about the jobs, employers, pay, locations, and required skills. It has fantastic possibilities for future visualization.


  1. Reddit

Reddit is one of the most well-known social media platforms in the world. For practically every issue, it contains communities that you may think of as subreddits. The thriving Reddit forums are a great place to test your web scraping prowess. You may search through your subreddits to see what comments your users have made about them. You can ignore this subreddit for a specific topic or piece of writing.

B) Project Ideas for Exploratory Data Analysis (EDA)

EDA is where data analysis begins. The exploratory data analysis stage is crucial since it enables you to comprehend your data and incorporates data visualization for enhanced exploration.

  1. Clusters of suicide

The worldwide suicide rates dataset includes information on suicide rates in several nations and the year, age, gender, population, and GDP. When carrying out your EDA, ask yourself: What patterns can you spot? Suicide rates increase or decrease among nations? What factors (such as age or gender) do you discover to be associated with suicide rates?


2. Report on World Happiness


This research illustrates the state of the world’s happiness as measured by the happiness index. For this assignment, we will use a variety of data analytic approaches to investigate some of these factors. Let’s start by looking at the regional happiness rankings for each nation. Whatever dataset you are using will eventually grab your attention. If the information is very abstract or of little interest to you, you’ll probably lose interest before you go very far. Remember what additional study you should conduct to find and understand fascinating trends or patterns.


C) Project Ideas for data visualization

A crucial component of the overall data science workflow is data visualization. It displays data after data analysis using large-screen monitors, linkage, dynamic blend, two- and three-dimensional flow charts, and chart design.

  • Word Clouds: 

Word clouds are unexpectedly helpful in natural language processing tasks. Words of varying sizes are arranged in a word cloud. These are the best techniques to remove text information from databases used to create tag clouds or text clouds, which may be found in blog articles. They can also assist users in comparing and determining if the two distinct text pieces’ language is comparable.

  • Covid-19: 

The idea looks fantastic in every portfolio, and the epidemic couldn’t be more fitting! Covid-19 data sets numbering in the hundreds are currently accessible on websites like Kaggle. How is the data displayed? Can you show where a few cases are using a global heat map? To compare known infections to anticipated infections, you might be able to design two bar charts that overlap one another.

Career opportunities in Data Analytics

One of the most well-known professions in the world is that of the professional data analyst. Due to the high demand and limited supply of skilled labor, data analysts command enormous pay and exceptional returns even at the entry-level. A variety of industries and enterprises employ data analysts. Any business that uses data does data analyst analysis.

How can I launch a Data Analytics career?

A wide range of essential technologies and tools, such as statistics, Python, R, Tableau, SQL, and Power BI, which are presently used in data analytics and data science, will be made available through the data analytics course in Chennai. After earning IBM certification in analytics, you should be able to handle today’s cutting-edge software and think statistically. Making the appropriate scheduling decision will advance your career and prepare you for a future with more chances.

Summing Up

The ideal strategy to demonstrate your skills in data analytics is to work on fresh, imaginative project ideas. You could only do that if you had prior sector-specific experience and overcame obstacles unique to that business. It’s the best method to stay upbeat and start data science and analytics projects.