Big Data is an exciting subject. It helps you find patterns and results you wouldn’t have noticed otherwise. This skill highly in demand, and you can quickly advance your career by learning it.
However, knowing the theory of big data alone won’t help you much. You’ll need to practice what you’ve learned.
But how would you do that?
You can practice your big data skills on big data projects. Projects are a great way to test your skills. They are also great for your CV.
What problems you might face in doing Big Data Projects:
Big data is present in numerous industries. So you’ll find a wide variety of big data project topics to work on too.
Apart from the wide variety of project ideas, there are a bunch of challenges a big data analyst faces while working on such projects.
They are the following:
Limited Monitoring Solutions
You can face problems while monitoring real-time environments because there aren’t many solutions available for this purpose.
That’s why you should be familiar with the technologies you’ll need to use in big data analysis before you begin working on a project.
A common problem among data analysis is of output latency during data virtualization. Most of these tools require high-level performance, which leads to these latency problems.
Due to the latency in output generation, timing issues arise with the virtualization of data.
The requirement of High-level Scripting
When working on big data analytics projects, you might encounter tools or problems which require higher-level scripting than you’re familiar with.
In that case, you should try to learn more about the problem and ask others about the same.
Data Privacy and Security
While working on the data available to you, you have to ensure that all the data remains secure and private.
Leakage of data can wreak havoc to your project as well as your work. Sometimes users leak data too, so you have to keep that in mind.
You can’t do end-to-end testing with just one tool. You should figure out which tools you will need to use to complete a specific project.
When you don’t have the right tool at a specific device, it can waste a lot of time and cause a lot of frustration.
That is why you should have the required tools before you start the project.
Too Big Datasets
You can come across a dataset which is too big for you to handle. Or, you might need to verify more data to complete the project as well.
Make sure that you update your data regularly to solve this problem. It’s also possible that your data has duplicates, so you should remove them, as well.
While working on big data projects, keep in mind the following points to solve these challenges:
- Use the right combination of hardware as well as software tools to make sure your work doesn’t get hampered later on due to the lack of the same.
- Check your data thoroughly and get rid of any duplicates.
- Follow Machine Learning approaches for better efficiency and results.
- What are the technologies you’ll need to use in Big Data Analytics Projects:
We recommend the following technologies for beginner-level big data projects:
- Open-source databases
- C++, Python
- Cloud solutions (such as Azure and AWS)
- R (programming language)
Each of these technologies will help you with a different sector. For example, you will need to use cloud solutions for data storage and access.
On the other hand, you will need to use R for using data science tools.
If you are not familiar with any of the technologies we mentioned above, you should learn about the same before working on a project.
Otherwise, you’d be prone to making a lot of mistakes which you could’ve easily avoided.
Big Data Project Ideas for Beginners:
We know how challenging it is to find the right project ideas as a beginner. You don’t know what you should be working on, and you don’t see how it will benefit you.
That’s why we have prepared the following list of big data projects so you can start working on them:
Topic #1: Classify 1994 Census Income Data
You will have to build a model to predict if the income of an individual in the US is more or less than $50,000 based on the data available.
A person’s income depends on a lot of factors, and you’ll have to take into account every one of them.
You can find the data for this project here.
Topic #2: Analyze Crime Rates in Chicago
Law enforcement agencies take the help of big data to find patterns in the crimes taking place. Doing this helps the agencies in predicting future events and helps them in mitigating the crime rates.
You will have to find patterns, create models, and then validate your model.
You can get the data for this project here.
Topic #3: Text Mining Project
Text mining is in high demand, and it will help you a lot in showcasing your strengths as a data scientist. In this project, you will have to perform text analysis and visualization of the provided documents.
You will have to use Natural Language Process Techniques for this task.
You can get the data here.
- Predicting effective missing data by using Multivariable Time Series on Apache Spark
- Confidentially preserving big data paradigm and detecting collaborative spam
- Predict mixed type multi-outcome by using the paradigm in healthcare application
- Use an innovative MapReduce mechanism and scale Big HDT Semantic Data Compression
- Model medical texts for Distributed Representation (Skip Gram Approach based)
Working on big data projects will help you find your strong and weak points. Completing these projects will give you real-life experience of working as a data scientist.
These projects will surely look good in your portfolio. If you want to get your hands on advanced big data projects, check out upGrad & BITS Pilani’s PG Certificate Program in Big Data & Analytics.
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