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How to Pave a Path Toward the Big Data Career

Big data has caused a significant impact on the current global economy.

By 2021, the global data market estimates to grow USD 67 million. Also, according to Andreessen Horowitz, about 90 percent of the data seen today has been generated in the last two decades. The world will be chasing talents skilled in big data. Grab the opportunity and embrace the skills needed to get a hold of a big data career.

Here’s what you need to follow.

  • Acquire big data skills

Big data skills will help you sharpen your career in big data.

Programming languages such as Python, Java, and C++. It is not mandatory to learn every programming language out there, however, having in-depth knowledge and programming skills in these languages will set your big data career on fire. Based on 2020’s AWS Salary Survey, the top programming languages in big data included Python, Java, and JavaScript,

Cloud professionals mentioned NodeJS, Ruby, Go, GoLang, and Terraform to be the hottest programming languages needed in 2020.

Quantitative analysis – since big data engineer deals with a large amount of number in their day to day lives, quantitative analysis is a major skillset in big data. For this, your background in mathematics and statistics needs to be strong.

Machine learning and AI – not a day goes by without hearing how AI has transformed the lives of many and caused significant impact amid the COVID-19 crisis. Reinforcement learning, logistic regression, decision trees, supervised and unsupervised machine learning, and adversarial learning are some of the skills big data professionals need to acquire. The more you’re able to offer to the company the more chances you have of getting a job soon.

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SQL and NoSQL databases – SQL is said to be the foundation of big data movement and is crucial to HadoopScala warehouses. NoSQL databases such as MongoDB have started replacing traditional SQL databases.

Data mining –as a big data engineer its high time to start investing in building the data mining kit with the industry’s favorite tools like KNIME, Apache Mahout, and Rapid Miner.

Data structure and algorithms – you should have solid skills in data structures such as red-back trees, binary trees, and hash tables along with algorithms like merge sort, heapsort, and quicksort.

Problem-solving – if you have a naturally analytical mind to work things out, you’re sorted to launch your career in big data. However, practice makes a man perfect, therefore do not lose to practice to hone these skills.

  • Work on projects

You can only learn by building. Start working on projects related to crime prediction, simulation, and prediction of traffic, analyzing nuclear physics data, fraud detection, modeling natural language, and many others. Employers seek candidates with hands-on experience. Being able to convince you’re capable of the job accelerates a higher probability of getting hired.

  • Build a work portfolio

Remember employers are only interested in our skills and not how flashy your resume looks. Ensure your portfolio has all the projects you’ve worked on. Having a portfolio of projects demonstrates your work to potential employers. It represents your expertise and skills in the field. In short, it is a useful tool in showcasing some of the best samples of your work.

A big data career if one of the best career fields to choose from today. With millions of job postings in data analytics and data science, more companies have started adopting big data. The perks of getting into big data will keep your profession in demand, get you to work with recognized brand names, offers higher salaries, and keeps your career at a safe spot.

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Many organizations have reported how recruitment in the big data field has become a challenge. With highly skilled talents in big data, obtaining jobs should not be a concern.

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