Big data is an exciting subject of information technology. It is applied in various domains to identify patterns and find results that are otherwise unnoticed. Big Data skills are very high in demand. Therefore, if you are keen on pursuing a career in big data analytics then you should start brainstorming on big data project ideas.
The Learnbay data Institute provides hands-on industrial training as well as theoretical knowledge on machine learning and artificial intelligence. Big data is a part of these computer science subfields. By exploring interesting big data project ideas, the learners can quickly grasp the concepts of this science.
So let’s get started on some of the popular big data projects that can boost your career immediately.
Classification of Census Income Data
One of the best big data projects to get started on is to build a model for the prediction of the income of individuals in any country. You can choose a classification parameter such as salary more than or less than $50,000 per year. Multiple factors determine the salary of a person. You might consider these para metres while collecting data on this project. Since the data for such a project is enormous, it becomes an ideal big data project.
Traveller Behaviour Analysis
One of the best big data project ideas is to analyse the behaviour of tourists. The big data collected can be used to find the most visited locations. These predictions can help in identifying the future demands of tourists. The steps involved in completing this project include a collection of text metadata, processing data to extract the list of interest from tagged pictures, clustering data to identify popular tourist locations, identification of photos uploaded by tourists, time series modelling to construct a time series data by keeping a count on the number of tourists every month.
This big data project focuses on the investigation in the long term and time-invariant dependence relationships in large data sets. The purpose of this project is to combat real-world problems based on cyber security. It exploits the vulnerability trends with complex multivariate time series data. This project establishes innovative and robust statistical frameworks. The learners gain a deep understanding of the dynamics and dependence structures.
Also read: What is Supervised, Unsupervised Learning, and reinforcement learning in Machine Learning
Health Status Prediction
The healthcare industries invest a lot in big data projects regarding health status prediction. This big data project idea is designed specifically based on the massive data sets on human health. The purpose is to create a machine learning model that classifies the users according to their health attributes. The classification categories include heart disease patients and non-heart disease patients. The decision trees machine learning methods of classification are employed for such a prediction tool project. The accuracy of this classification ML model depends on the feature selection approach.
Selecting the most appropriate candidate for a particular job can be challenging for the HR department of any company. This big data project invests time and energy to collect the relevant data of the applicants and select the best one accordingly. The major steps involved in such a project are identification of Job families in the given data set, identification of homogeneous groups that are highly valued, characterising job families according to the level of competence required for each skill set.
One of the trending deep learning applications is the detection of fraud in a system. This deep learning or big data project idea is regarding the reliability of users. The purpose is to calculate the reliability factor of users from the big data. The data is divided for trustworthiness into familiarity and similarity trustworthiness. The model classifies people into small groups according to the similarity trustworthiness factors. The trustworthiness of each group is calculated to reduce the computational complexity. The project allows us to identify the trust level of a particular group.
Also read: Regression Techniques in Machine Learning
Forecasting Electricity Price
This big data project is used by several electricity providing agencies and government bodies. The idea behind this project is to forecast the prices of electricity by collecting big data sets. The SVM classifier of our model is used for this purpose. The model includes irrelevant and redundant features during the training phase in the SV and classification hence reduces the accuracy in forecasting. To counter this problem, methods such as great correlation analysis and principal component analysis can be used. These analysis methods select only the important features and eliminate the unnecessary elements. This step ensures accuracy in the model classification.
Analysing Crime Rates in the City
You can collect data on criminal records and try to find patterns and create models and later on validate your models. Collecting data or big data from law enforcement agencies and considering various parameters such as type of crime, time of crime, occurrence or frequency of crime, and many more. Such a model can help in predicting future events and eliminating the number of crimes in the city.
Rigorous Text Mining
One of the most lovable big data projects for beginners is the deep learning project. Text mining is a very popular and in-demand application. Here, the learners showcase their strength as data scientists. In this project, text analysis and visualisation of the provided data is done. Techniques such as the natural language process are employed for this task.
It is a GPS trajectory-based project that identifies travelling routines in a city or urban area. Based on the GPS trajectory data obtained, future events can be detected. The data interpolation technique is employed to identify the missing values in the GPS data.
More Project Ideas
You can also go for the following big data projects if you accomplish the above-mentioned projects.
● Prediction of missing data by using multivariableeventsFreely available databases time series
● Modelling medical text for distributed representation
● Using innovative MapReduce mechanisms and scale big SDT semantic data compression
Things To Remember
● Before starting to work on any of the above mentioned big data projects, keep the following pointers in mind.
● Use the right set of hardware and software tools to ensure a smooth experience
● Check the data thoroughly and remove duplicates and unnecessary elements
● Apply the machine learning algorithms for better and efficient results
The recommended technologies to be used during big data projects are:
● Freely available databases
● R programming language
● Cloud solutions
These technologies help deal with different types of projects in different sectors. For example, Cloud solutions are needed for storage and access to data. R programming is used for statistical analysis.
If you are unfamiliar with any of the above-mentioned tones, then you should first try to gain some experience in using them.
Also read: Model vs Algorithm in ML
Challenges Faced During Projects
Some of the aspirants might face a bunch of challenges while working on these projects. The possible problems to be encountered by them are mentioned below.
Since the data is huge, the processing might take a lot of time. The output latency at the time of data visualization can be challenging. High-level performance tools are mandatory to overcome this problem.
It might be difficult to monitor the real-time environment since there are no solutions available for this purpose. Familiarise yourself with the technologies that help you in getting over the monitoring issue.
Big data analytics projects become challenging when problems arise during the scripting. Many tools require high-level scripting that students are unaware of. Seeking expert advice is the best possible solution for this challenge.
You might have the data sets but sometimes the lack of proper tools can completely break you down. Try to take those projects for which you have the right tools available. Try to avoid any frustration since it can affect the project outcomes.
Huge Data Sets
Sometimes the data may be too big to handle. This might pose a great challenge where data needs to be processed and cleaned before use. By employing the right tools and strategy, the data can be manipulated effectively.
While working with health data and similar private data, you have to be extra cautious. Maintain the security and confidentiality of the data. The leakage of information during a project is not a good sign.
If you are an aspiring Big Data analyst or Big Data scientist, the expert guidance of Learnbay can help you in achieving that dream. Learnbay provides you with the following courses with professional training:
1 Data science certification course
2 Artificial intelligence certification course
3 Data science and AI for managers and leaders
Here we have listed some of the best big data project ideas for learners. These projects are best for beginners, intermediate, and advanced level learners. By practising on such big data projects, the aspirants can gain confidence in tackling many advanced projects in future. It is recommended to learn from these projects to enhance big data skills.
The application of algorithms in these projects will help you in identifying your strengths and weaknesses. It provides a real-life experience of working as a big data engineering or big data scientist.
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