Big data is quickly becoming a sought-after IT field. It is an interesting subject that helps you to uncover patterns in large sets of data. Big data skills are in high demand, and this career path has a promising future. Employers are constantly on the lookout for skilled big data specialists. So, if you are an upcoming big data professional, the best way to advance your career is to work on big data projects.
Data science projects provide a means of putting theoretical concepts into practice. In this article, we will discuss some exciting big data project ideas that you can try out to put your big data skills to the test. These projects are divided into three categories: beginner, intermediate, and advanced. You should experiment with these projects based on your skill level.
5 Skills That Big Data Projects Can Help You Practice
Big Data projects offer a quick way to gain hands-on experience and advance your education. Theoretical knowledge alone will not suffice to develop your skills and proficiency in big data. Therefore, it is critical to practice with projects that mimic a real-world work environment. Here are a few examples of the big data skills that projects can help you practice.
- Data Analytics. This is one of the most important big data skills. Big data experts should possess analytical skills to understand complex data and solve problems using data science tools.
- Data Visualization Skills. This is the ability to interpret and present data to convey a particular message. Being able to visually present data analysis plays a major role in a big data career. Anyone interested in a career in big data should develop their data visualization skills.
- Programming Skills. Big data projects can improve your knowledge and expertise in data analytics and programming languages such as Scala, C, Python, and Java. To be considered an expert in big data, you must have a solid understanding of the fundamentals of algorithms, data structures, and object oriented languages.
- Data Mining. Learning data mining through projects can provide you with practical knowledge in data mining concepts and data mining tools like KNIME, Apache Mahout, or Rapid Miner. Having strong data mining skills is fundamental to succeeding in a career in big data.
- Use of Cloud Services. Advanced projects can introduce you to the use and application of public and hybrid clouds. As you must utilize clouds to store data, it is important to be familiar with cloud software providers such as Amazon Web Services (AWS), Microsoft Azure, OpenStack, Vagrant, Docker, and Kubernetes.
Best Big Data Project Ideas for Beginners
Data science could be difficult and confusing to learn for beginners. However, it becomes easier with constant practice. Taking on projects that expose you to big data is the best way to grasp the various concepts and terminologies and build your skills. Here are a few big data projects for beginners.
Health Status Prediction
- Big Data Skills Practiced: Data Analytics, Programming
This project involves gathering information on different health conditions such as breast cancer, diabetes, and Parkinson’s disease. By compiling and analyzing this data in datasets, we can build a system to identify risk factors and predict the likelihood of these diseases.
Fake News Detection
- Big Data Skills Practiced: Programming, Data Analytics
Another project to consider is the fake news detection project. The goal of this project is to determine the authenticity of information found on social media platforms. You can achieve this with Python programming. You can employ TfidfVectorizer and PassiveAggressiveClassifier to analyze news and classify real news from false news.
Forest Fire Prediction System
- Big Data Skills Practiced: Data Mining, Data Analytics
The forest fire prediction system employs data science capabilities to predict and control the destructive nature of wildfires. You’ll need to utilize k-means clustering to identify major fire hotspots and the probability of future wildfire occurrence. For more accurate predictions, you may also include meteorological data to identify the seasons and common times when wildfires might occur.
Breast Cancer Classification Program
- Big Data Skills Practiced: Programming, Data Analytics
If you’re looking for a big data project in the healthcare industry, this is the one to take on. The breast cancer detection system identifies cancer at an early stage by checking and analyzing patients’ databases. This enables patients to take necessary preventive measures.
Real-Time Traffic Analysis
- Big Data Skills Practiced: Programming, Data Analytics
This project entails the creation of a system that monitors traffic on major roads and recommends alternate routes. You can instruct the system to use real-time analysis of traffic to program traffic lights so that they remain green for a longer period of time on busier roads and for a shorter period of time on free roads.
Best Intermediate Big Data Project Ideas
Taking on a few beginner projects will help you to develop proficiency in the fundamental concepts of big data. When you feel confident in your abilities, you can advance to intermediate projects. Intermediate projects take you out of your comfort zone and introduce you to more advanced big data applications. Here are a few ideas for intermediate big data projects.
Speech Emotion Recognition
- Big Data Skills Practiced: Programming, Data Analytics
This project takes students through the use and applications of different libraries. Speech emotion recognition (SER) is a system that analyzes human speech with librosa to pick up notes that relate to human emotion and affective states. This project may be a bit complicated because human emotions are subjective to each person.
Gender and Age Detection with Data Science
- Big Data Skills Practiced: Data Analytics, Data Visualization
In this deep learning project idea, you will create a system that processes images to predict the gender and age group of a person. You’ll learn to use computer vision networks and apply the principles to build a convolutional neural network. You will also utilize models trained by Hassner and Gil Levi to analyze the Adience datasets.
Building Chatbots
- Big Data Skills Practiced: Programming, Data Mining
This is a simple mini-project that you can try out that uses artificial intelligence. It guides you through the process of creating a chatbot using Python programming. Chatbots are used by businesses to quickly respond to massive datasets of customer queries and messages. Chatbots analyze client messages and respond appropriately.
Analysis of Airline Datasets
- Big Data Skills Practiced: Data Analytics, Data Visualization
This is another data science project idea that is perfect for intermediate students to practice their skills. Airlines employ detailed analysis techniques to monitor air routes and maximize efficiency. For this project, you’ll need to consider a wide range of factors such as the number of people flying over a certain period, delays, and the best days of the week to avoid delays.
Driver Drowsiness Detection in Python
- Big Data Skills Practiced: Data Mining, Data Analytics
Thousands of accidents happen every year due to drivers falling asleep as they drive. In this project, you will design a system that can identify drivers and wake them up with an alarm. You will use Keras and OpenCV. Keras helps us to analyze the face and the eyes, while OpenCV allows us to detect drowsiness by checking if the eyes are open or not.
Best Advanced Big Data Project Ideas
If you consider yourself an expert or have advanced mastery of big data techniques, you should try out some advanced big data project ideas. Here are a few examples.
Build a Scalable Event-Based GCP Data Pipeline
- Big Data Skills Practiced: Programming, Use of Cloud Services
This is a technical project involving designing an event-based data integration system using Dataflow on the Google Cloud Platform. When an event occurs, the system automatically updates the data. You’ll use Python programming languages and other services such as Cloud Composer, Google Cloud Storage, Pub-Sub, Cloud Functions, BigQuery, and BigTable.
Generating Image Captions
- Big Data Skills Practiced: Data Mining, Data Visualization
It is unusual for an image to be posted on social media without related image captions. This deep learning project idea involves handling large datasets that correlate with images and captions. To analyze the image, you will need to use deep learning techniques and image processing. Then use artificial intelligence to generate appropriate captions for the image.
Snowflake Real-Time Data Warehouse Project for Beginners-1
- Big Data Skills Practiced: Programming, Use of Cloud Services
If you’re looking for a challenging project, this is it. Snowflake is a data warehouse company that makes use of cloud computing and data storage services. This project mimics the Snowflake architecture. You’ll learn how to use SQL to create a data warehouse in the cloud for a business.
Web Server Log Processing
- Big Data Skills Practiced: Data Analytics, Data Mining
This project is ideal for advanced big data analysts because it involves processing a web server log to extract data that can be used for web page ads and search engine optimization (SEO). A web server log contains a list of page requests and other browsing activities.
Log Analytics Project with Spark Streaming and Kafka
- Big Data Skills Practiced: Data Analytics, Data Visualization
Log analytics is the process of evaluating and analyzing logs from programming technologies. A log contains a list of messages that describes the operation of a system. In this project, you’ll use real-world production logs from NASA Kennedy Space center WWW servers to perform log analytics with web visualization apps like Apache Spark and Kafka.
Electricity Price Forecasting
- Big Data Skills Practiced: Data Analytics, Data Visualization
This is one of the most exciting big data project ideas. It involves designing a system that predicts electricity prices by leveraging big data sets. You will need to use an SVM classifier to analyze the data and predict future electricity prices. To improve the accuracy of the system and eliminate irrelevant data, you would have to employ Grey Correlation Analysis (GCA) and Principle Component Analysis.
Big Data Starter Project Templates
A starter template is a guide that contains source codes that can be easily modified to meet the needs of your project. It simplifies concepts so you don’t have to start from scratch. You can use big data starter templates to assist you during your projects.
- Classify 1994 Census Income Data. This template involves the development of a model that analyzes a dataset to predict if a person’s income in the US is more than $50,000.
- Analyze Crime Rates in Chicago. This template is a dataset analysis of reported crime in Chicago from 2001 to the present.
- Text Mining Project. This is a template of statistical text analysis on a Star Wars movie script. It employs data visualization and natural language process techniques.
Next Steps: Start Organizing Your Big Data Portfolio
A big data portfolio highlights your skills, experience, and expertise. It works just like a resume. However, it also includes projects that demonstrate that you have the skills to succeed in getting a job in data science.
When you have a well-packaged portfolio that advertises your technical expertise, you have a higher chance of landing the job. Here are some tips to help you build your big data portfolio.
Include Your Best Big Data Projects
You must demonstrate your best projects, the ones you are most proud of, and effectively describe your skills to potential employers. You want your employer to have a clear picture of your abilities so that you can present yourself as a qualified candidate.
Showcase Your Actual Projects
Simply listing your projects in your portfolio is insufficient, you must also include the work itself. Include a link to the actual, launched projects in your portfolio. You can accomplish this by using a free software repository such as Github, Bitbucket, or Gitlab. This would persuade prospective employers of your abilities even more.
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Include Relevant Projects
When applying for a job, it is best to include projects relevant to the job role. You should include relevant project details so that interviewers can assess your abilities. This increases your chances of being chosen as the best candidate.
Big Data Projects FAQ
The three types of big data are structured data, unstructured data, and semi-structured data. Structured data is highly organized and defined by parameters. Unstructured data is any data set that contains less than 20 percent structured data. Finally, semi-structured data is a category of data that falls between structured and unstructured data.
There are six big data analysis techniques, namely, A/B testing, Data Fusion and Data Integration, Data Mining, Machine Learning, Natural Language Processing, and Statistics.
There are four types of analytics in big data. They are Descriptive Analytics, Diagnostics, Predictive Analytics, and Prescriptive Analytics.
The best big data technologies are Apache Hadoop, Apache Spark, MongoDB, Cassandra, and Tableau.
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