Top Data Analytics Projects

“This is my favorite part about analytics: Taking boring flat data and bringing it to life through visualization” - John Tukey (American Mathematician and Statistician)

The above mentioned statement made By John Tukey – known for the development of the box plot and Fast Fourier Transform Algorithm – points at three different ideas: Data Extraction, Data Analytics and Data Visualization.

Raw data is available in abundance around us. Data Analytics helps in deriving meaningful insights and valuable correlations from this “flat data”.

Data Visualization helps in the presentation of findings in visually appealing and understandable forms which help in driving business decisions.

Data Analytics Projects are a form of this Data Visualization. A Data Analytics Project helps an individual to showcase his analytical skills on a specific issue; thereby convincing his potential employer of his potential as a Data Analyst and thereby building his Data Analytics portfolio.

In this blog, we will look at some of the top Data Analytics Project Ideas which could help you grab this coveted job. However, before moving into the question of the Data Analytics Project for Students, we will consider certain other aspects of the domain as well.

What is Data Analytics?

As the name suggests, Data Analytics implies the process of making sense of data. It is a discipline which deals with the management of data through its collection and storage as well as, with the techniques, processes and tools, which help in analyzing it.

The main purpose of Data Analytics is to discover patterns, valuable correlations, unseen trends, and consequently, extract meaningful insights which could help in undertaking business decisions, making predictions as well as improving its efficiency.

For a more detailed understanding of Data Analytics, check out our blog on “What is Data Analytics?”

Components of a Data Analytics Project

In this section, we will look at some of the components of a Good Data Analytics Project. These components are largely in terms of what exactly an interviewer looks for in data analysis projects and what they find impressive. So, let us look at what these components are:

• Real Data

Projects involving data produced in real-time or real data generated by users, give a sense to the person examining it that the student has an idea of working with timely and relevant data. Data sets which are too old are considered redundant.

• Exploiting Modern Technologies

This component of a good Data Analytics Project pertains to the ability of a student to make use of technologies which could help him to extract real data. This can involve using API’s as well as Databases in the Cloud for storing data. Data Analytics Projects which are considered to be good should be able to give the interviewer a sense that the student knows how to use the API in order to acquire data.

This might include geolocations, real-time updates, text and numbers as well as timestamps and dates for records. It is important to remember that working with APIs give a sense of your skill in using libraries, data structures and dictionaries as well as in configuring APIs in your code.

Additionally, if you are able to showcase that you are capable of building a data pipeline with a cloud provider, then it will definitely be a huge plus point and will help to set you apart from others.

• Model Building

Building Models is definitely considered to be an important consideration in any Data Analytics Project Idea. However, it is simply not enough to learn to build models. It is equally important to be absolutely clear about the things which made you decide upon a particular model for your project.

Thus, while using a particular model for your Data Analytics Project, you should be clear about why you chose that model, what was the objective you sought to achieve with that model, what were the assumptions of the model, how did you attempt data cleaning, what kind of validation tests did you execute on the data, and so on.

This is because the examiner is quite likely to be more interested in your thought process than the mere performance of the models.

• Acquiring Validation

It is not simply enough to complete a Data Analytics Project. Good Data Analytics Projects contain findings which have an impact in terms of helping others to take decisions. If you are able to convince the interviewer that people care about your work and find it valuable by sharing the feedback received on your project; it would definitely be an impressive act.

Levels of Data Analytics Projects

You might find yourself surrounded with scores of Data Analytics Project Ideas. Some in the form of best Data Analytics Projects for Students; while others are projected as top Data Analytics Project Ideas which can help you get a job.

The point to remember is that it is important for you to assess yourself first in terms of the level of a Data Analytics Project that you are comfortable with, before taking the final call. So what are these levels of Data Analytics Projects?

Beginner Level

This level covers Data Analytics Projects for Students who are essentially beginners in the field of Data Analytics. These Data Analytics Projects involve simple algorithms and do not depend on heavy application techniques.

Intermediate Level

This level covers projects entailing medium to large data clusters. This implies that if you have a sound understanding of Machine Learning techniques and the concept of Data Mining, then you can proceed with Data Analytics Project Ideas at the Intermediate Level.

Expert Level

This level covers projects entailing high-dimensional data and is appropriate for those who are already experts in the field of Data Analytics. If you feel that you do possess the appropriate blend of expertise and creativity, then you might consider these advanced Data Analytics Project Ideas.

Data Analytics Project Ideas

Beginner or Easy Level Data Analytics Projects

Exploratory Data Analysis Projects or EDA

EDA is often considered to be the genesis of data analysis as it helps one to make sense of data as well as visualize it for better exploration. For the purpose of Data Visualization, students can opt for heat maps, histograms or scatterplots.

Exploratory Data Analysis can help students to highlight outliers and expose unexpected results. The project can be done with Python, a good source of EDA dataset can be IBM Analytics Community and for the purpose of packages, students can opt for NumPy, matplotlib and pandas.

Sentiment Analysis

This kind of a Data Analytics Project is used for acquiring the opinion and sentiments of the people on a particular subject. It is also known as Opinion Mining and is backed by Artificial Intelligence.

It is a common form of natural language processing task which helps in evaluating positive or negative polarities (binary) of the individuals based on their sentiments, or if it is in the form of multiple categories (happy, sad, angry, confused and so on). This kind of Analysis is widely used by modern businesses for social media monitoring for assessing the perception of the customers over the brand, or for competitor analysis.

The project can be done with R, a good source of dataset can be with Jane austen's dataset and for the purpose of packages students can opt for tidytext package.

Fake News Detection

This can be an outstanding Data Analytics Project Idea. Fake news has evolved as a huge nuisance in current times and this Data Analytics Project involves building models with the help of Python language which can help in identifying false/hoax information from real journalism.

The real-time machine learning model can be built with the ‘PassiveAggressiveClassifier’ and ‘TfidfVectorizer’ for classifying fake and real news into separate categories.

The project can be done with Python, a good source of dataset can be News.csv and for the purpose of packages students can opt for NumPy, Scikit-learn and pandas.

Intermediate Level Data Analytics Projects

Chatbots

A chatbot can be considered as a smart program which triggers a real interaction with consumers through a chat interface. These chatbots respond to any spoken or written queries and are able to comprehend conversations. Thus, they have become crucial for automating customer service, along with saving time and resources.

With the ability to respond with a mapped reply, they are based on Data Science, Machine Learning and Artificial Intelligence. If you plan to take up this idea as your Data Analytics Project you can train the chatbot with the help of ‘Deep Learning Techniques’.

Recurrent Neural Networks, as also the intent JSON datasets, happens to be the common methodology for the purpose. The implementation can be carried out with the help of Python.

Age Prediction and Gender Detection

This is one of those interesting Data Analytics Project Ideas which puts your Computer Vision and Machine Learning skills to test. Among the Data Analytics Projects, this is considered to be an extremely practical one which tries to predict age and detect gender through the analysis of a single image.

Gender classification is generally in binary terms (men or women), while age is classified among the ranges. However, conditions like makeup, facial expressions and lighting can make the task quite challenging and thus, you need to be very particular about the model which you build.

This can be one of those Data Analytics Projects where you learn the application of the Convolutional Neural Networks as well as the usage of Python with the OpenCV Package.

Speech Emotion Recognition

This project which aims at recognizing human emotion from their verbal communication is quite a popular topic for Data Analytics Projects. Speech is considered to be a fundamental form of expression which embodies various emotions as well. Understanding this emotion helps in restructuring services, actions and products in the pursuit of a better and more personalized service to the consumers.

If you want to proceed with this Data Analytics Project Idea, you will be required to detect and derive emotions from human speech available in the form of multiple audio files. The project can be done with Python, a good source of dataset can be Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) and for the purpose of packages students can opt for NumPy, Scikit-learn, Librosa, PyAaudio and SoundFile packages.

Expert/Advanced Level Data Analytics Projects

Credit Card Fraud Detection

The usage of credit cards has increased tremendously over the years and so has the number of credit card frauds. However, with the help of technologies like Data Science, AI and ML, organizations are being able to detect and intercept these frauds.

The purpose of this Data Analytics Project is to identify transactions on a credit card as being genuine or fraudulent. This is usually done through analyzing the spending behavior of the customers as well as zoning into the location of those spending for detecting cases of fraudulent transactions.

The project can be done with R or Python, a good source of dataset will be the transaction history of the customers and you will be required to work with Logistic Regression, decision trees and Artificial Neural Networks.

Web Show/Movie Recommendation

The next time you log into your Netflix account and find yourself being recommended a particular movie or web series which you have been thinking of watching; you might just feel that this OTT platform seems to be reading your mind.

The reality is that such platforms use an advanced recommendation system which considers several indices like previously watched content, age, frequently watched genre and so on, and feeds them into a ML model, which helps in generating by far the most likable recommendation of a show for the user.

If this particular Data Analytics Project Idea seems to excite you, then you can proceed with R, a good source of dataset can be MovieLens dataset, and for the purpose of packages you can opt for ggplot2, data.table, recommenderlab and reshap2.

Customer Segmentation

With the growing popularity of Digital Marketing and a shift to a client centric model of business operation, companies are increasingly seeking to streamline their marketing activities by running highly tailored campaigns in terms of reaching out to the right audience.

If you wish to proceed with this Data Analytics Project Idea, you will be required to make use of unsupervised learning for grouping customers into groups and clusters based on factors like gender, age, interests, location and so on.

You can opt for Hierarchical Clustering or K-based Clustering, or proceed with Density-based Clustering or Fuzzy Clustering. The project can be done with R and a good source of dataset will be Mall_Customers dataset.

Conclusion

In this blog, we have tried to look at 9 exciting and popular Data Analytics Project Ideas. The topics for Data Analytics Projects covered here is by no means exhaustive and there is a huge collection of topics which can be chosen beyond those mentioned here.

What is important to understand is that, Data Analytics is one of the most in-demand domains within the tech industry and holds innumerable opportunities for the future. As an individual aspiring to grab these coveted positions as Data Analysts through a good Data Analytics Project, you should equally be prepared to face the challenges which it might entail.

Seeking to understand the future potential of this domain?; check out our blog on "Future of Data Analytics"

We, at Syntax Technologies, provide you with the commendable opportunity to develop skills in line with the demands of the Data Analytics field. Read more about our Data Analytics and Business Intelligence course here: