Big data and data analytics has taken the IT industry by storm in recent years! Data is what has made our lives a lot simpler and easier in recent years. With a rapid proliferation in the number of internet users and the trend of moving everything to the cloud, the amount of data has ballooned leading to a number of new opportunities emerging in this sector.
If you are studying in college/looking for a job in big data, here are the trends that you need to look out for in big data:
Internet of Things
The Internet of things is a fast-growing sector that involves connecting devices of myriad types. IOT and big data are closely intertwined with more devices being connected to the internet and which in turn generating huge amounts of data to process. As students, there are a number of data science projects that could be undertaken in IOT. The challenges in the industry are myriad, with a huge number of devices entering the market every year, and the need to connect the devices seamlessly. This is all the more reason, why you should get your hands dirty with an IOT project.
Computing has undergone a sea change ever since Moore’s law and is now advancing towards quantum computing where the number of calculations that can be undertaken in a second would be huge. This type of computing would be especially useful in handling massive datasets. Quantum computing involves identifying patterns in data and optimizing the process of data handling. Undertaking a data science project in quantum computing can be highly rewarding and employers take a lot of notice since the field is still nascent.
Big data in deep learning
The win of AlphaGo against human players has brought awareness in the progress of deep learning to the mainstream. Knowledge in python is highly useful in applications for deep learning. There are companies like EduGrad that offer a number of python training courses for the student community. Employers also look for projects as a way of measuring the proficiency of an individual.
Big data in Cloud
Cloud is a very hard thing to ignore when speaking of big data. Data analytics is done a lot easier when the data is moved from the local device to the cloud. There are a myriad of advantages in moving data to the cloud and if you are looking for a good way to start, you could get some basic training in data analytics and undertake some practical projects.
Natural Language programming
Chatbots and NLP applications are a very exciting use case in which large datasets can be used. Python is the main language used for natural language processing and there are a number of useful resources to start learning python. With the rise of Google Assistant, Alexa and a number of chat agents, there are a large number of opportunities for people passionate in making our lives simpler using bots. Big data is especially used here to train the bot to give better responses over time.
Big data and open source
With open source gaining widespread acceptance, there are many tools like Hadoop, Cassandra, and Apache that are being learned by students and professionals alike. Tools like Hadoop are extremely good at handling extremely large datasets as everything is done in cloud storage. Hadoop is also the foundation for multiple use cases like statistical analysis, business and sales analytics. Data evaluation in an optimized way is very important and open source is the perfect way to process huge data sets.
With video gaining a lot of traction amongst the general public due to the widespread availability of high-speed internet, streaming analytics has a lot of opportunities in recent years with tons of data to be analyzed. Be it YouTube or Netflix or Amazon Prime, each company has its own challenges and need professionals who can make sense of data and optimize their product offerings further.
Big data as a way to hire better
While there has been a couple of controversies in using data sets to hire for companies, big data has been immensely useful in hiring people that can adapt to the company culture. With HR professionals getting a huge number of resumes, big data comes to the rescue by using past information to classify resumes better. Big data also identifies a person’s individual talents and can help the HR understand what role suits him/her best. If you are adept at data analytics and handling huge datasets, companies would pay a dime to optimize their recruiting process.
Big data: Where to start?
While the amount of information overload may be dizzying to many, it is important to remember to start slow. You can start by learning python, undertake data analytics courses and do projects on your own to bridge the gap between theoretical and practical learning. Employers would prefer someone has practical/application knowledge to someone with only theoretical knowledge.
At EduGrad, we have a 4-week training course to people who are passionate about deep learning and projects that you can do in your spare time. Be it data scraping, data visualization or data errors we help you hone various skills in data science.