5 Best Data Analytics Projects for Beginners

 Data analytics is a crucial component of data science, enabling companies to gain a more comprehensive understanding of their business operations through the utilization of data analytics. Individuals need to complete specific data analytics projects before beginning their careers in the field. However, choosing which assignment you must get done is a conundrum.

It often looks easy at first when you’re starting with a data analysis project. Finding a project that is in demand and helps enhance your portfolio is also a significant task. Fortunately, we have created a list of data analytics projects you can do as beginners. These projects will also help develop new skills and guide you toward a professional career.

Need for Data Analytics Projects for Beginners

People entering the data analytics field for the first time often face a dilemma. As beginners, you don’t possess enough experience, but recruiters look for experienced candidates for data analyst positions. So, what is the quick way out of this scenario? In such cases, data analytics portfolios become useful.

Make sure you include projects in your portfolio that display your expertise and skills within the field context. A portfolio consisting of relevant projects ensures employers of your knowledge and convinces them of your proficiency.

Now, the question arises: what role does data analytics play in business scenarios?

Role of Data Analytics

• Finding hidden trends and patterns in data goes a long way in informing business decisions. The data gathered is analyzed according to business needs to uncover meaningful insights.
• Performing market research and analysis is also a significant strength of data analytics. Analyzing a company’s market value helps develop efficient strength and weakness reports.
• Data analytics also helps generate reports based on the analysis. It may include dashboard reports, aggregate reports (complex bills, etc.), or general reports (data entry reports, query reports).
• The customer is king. So, in most cases, data analysis reports help enhance the customer experience. It also creates better business requirements.

Components of a Data Analytics Project

It is essential to understand the requirements of an interviewer from a project before you start working. An interviewer judges a candidate on their analytical, coding, and technological skills. Possessing these skills further helps in achieving your goal of becoming a reliable data analyst.

The components of a data analytics project are:

• Working with real data
• Leveraging modern technologies (APIs and databases in the cloud)
• Building models
• Getting Validation

Let’s explore some projects that add value to your portfolio and help build a strong portfolio.

Data Analytics Projects for Beginners

Color Detection Project

This project identifies the color of any object in an image. This type of project helps in applications using image editing and drawing features. Color detection aids in the easy recognition of things in a snap.

There are vast amounts of colors in the world (up to 16 million colours) based on RGB (Red, Green, Blue) values. Hence, this is a perfect project for beginners, as they can develop an interactive application that precisely determines the colours in an image.

Real-life use case

Colour detection has a broad range of industrial usage in automation, food, tactile, printing, and more. Colour sensors are utilized in such industries to identify coded markings, grade coloured products, and locate data codes or adhesives on packages. The sensors are capable of identifying single or multiple colours.

For example, the food industry uses colour sensors to measure the colour change in plastic warps where meat is stored. It helps detect if the meat quality has become worse. Colour sensors can also help to control the temperature of coffee bean roasting.

Social Media Monitoring

Social media has grown to be of much importance in these days. It helps a business establish a meaningful relationship with its customers. However, it may also tarnish the brand image. Even a single comment or poor review can leave a bad mark on a company’s reputation. So, how does social media monitoring help?

The social media monitoring project evaluates user comments related to brands and services. You will find people’s thoughts and opinions about products, customer service, industry, competitors, and more. Brands can find meaningful ways to improve their performance and image using this project.

Real-life use case

Social media mentoring can help you in the following ways:

• Using sentiment analysis to understand user’s feelings (positive, negative, or neutral) through their online reviews.
• Identifying the ROI (return on investment) on your brand strategies. Evaluate if your money is paying off and how it is working.
• Finding proper keywords and hashtags to enhance online strategies and bring in new customers.
• Evaluating trends and acting on them accordingly. For example, jumping on trending memes, themes, topics, and songs in real time can boost your brand awareness.
• Analyzing your brand’s online perception vs. your competitors through online conversations.

Fake News Detection

The internet is so vast that anything can be passed off as genuine. So, how can you evaluate if something is real or fake online? Well, using Python, of course!

This Python project can help you find out fake news from real ones. It can detect false news or hoaxes that follow a political agenda. It uses Python to measure the genuineness of news stories quickly. It analyzes social media platforms and online media that spread such news. Furthermore, it will help if you become familiar with terms like TDFIDFvectorizer, fake news, and PassiveAggressive classifier beforehand.

Real-life use case

Social media platforms and news outlets can quickly and easily find fake news from the vast amount of information generated daily. ML algorithms make the whole process faster for humans. By analyzing sources, wording, and social media networks related to the news, ML algorithms can accurately locate fake news.

Exploratory Data Analysis (EDA) Projects

EDA is an essential part of data analysis. EDA analyzes the framework of the data to find trends and features. The project helps understand data cleaning, find variables and anomalies, and test basic principles using data visualization methods and statistical graphs.

It uses the Python language due to its many algorithms that speed up the work. EDA can become a tough and time-consuming project for data analysts to complete, but it is also a satisfying project.

Real-life use case

Marketing: The EDA project helps answer marketing questions. Such as, ‘Why are users not interested in purchasing a product?’ or ‘Why a certain strategy didn’t work?’ Using EDA, analysts can understand the context around such variables and take action accordingly.

Healthcare: EDA helps spot trends in massive data sets. Hospitals, medical departments, and networks use electronic medical records (EMRs) to store their data. Data mining systems test EMRs to find vital data about chronic diseases in patients, such as kidney disease.

Sports: Sports analysts use EDA to locate players and teams that have been highly successful. They can also find factors contributing to their success or loss. They can evaluate this data to select the players or teams that should be chosen for endorsements.

What’s Next?

A solid data analysis portfolio helps recruiters evaluate your skills. So, make sure you explain the data product or model in each project. You may explain how you overcame a problem, mention the tools you used and why, and also include proper visuals to explain the outcomes.

Your portfolio should include many projects, like exploratory data analysis, sentiment analysis, and more. You can upload the projects on GitHub. Set your task to “Public” in Tableau if you’re using it for data visualization so potential employers can find it online.

Be sure to hone your skills to stay ahead of the competition. If ever you require the assistance of expert mentors in your projects, then take the time to check out Learnbay’s data analytics course, designed per industry standards. You get dual certifications from IBM and Microsoft. Plus, mentors help you complete real-world projects to include in your portfolio.