Top Big Data Analytics Skills that Aspirants Should Know in 2022

Big data analytics skillsOrganizations looks for versatile candidates with amazing big data analytics skills.

In the digital world, people are using technology at every end. Starting from social media apps to smart home technologies, our modern life is filled with disruptive devices and tools that collect data. Owing to the increasing inflow of big data, organizations are also using them as a reliable source to sort customers’ needs. As a result, more companies are looking for big data professionals with amazing skills. A report by LinkedIn has revealed that there is a shortfall of data analysts in many of the US cities. The national shortage of skilled professionals in data science and big data analytics domains has reached 150,000. The World Economic Forum also revealed that data analysts are needed across many industry verticals. Although the demand is increasing, organizations are not recruiting anybody who has a data analytics certificate. Rather, they look for versatile candidates with amazing big data analytics skills. Since data analysts have to deal with opportunities in sales, marketing, human resources, and other hectic business areas, it is important for the company to employ an all-in-all candidate who has diverse skills. In this article, IndustryWired has listed the top big data analytics skills that will help you land an amazing job in 2022.

Top Big Data Analytics Skills to Learn

 

Analytics Knowledge

Analytics is truly the heart of most of the big data routines. Therefore, mastering the analytics skills and becoming a pro in handling analytics tools will keep your demand afloat in the market. You should also combine your mathematical and scientific knowledge with technology to deliver good results. Learn some unique ways to use analytics tools to solve real-world business problems.

 

Programming

Traditionally, big data professionals were not asked to learn to code. But since the digital sphere is evolving, only big data analysts with programming skills can survive. The inflow of data is very constant and unstoppable. Therefore, data professionals with minimum programming knowledge won’t be able to deal with them effectively.

 

Computational Frameworks

Computational frameworks or tools like Apache Spark, Apache Storm, Apache Samza, MadPreduce, Hadoop, and ApacheFlink are at the heart of every big data process. Learning them has become a mandatory move in the digital ecosystem.

 

Data Mining and Machine Learning

Big data is a vast field that houses disruptive technologies like data mining and machine learning. Therefore, mastering these two trends will keep you ahead in the market. However, data mining and machine learning are just a part of analytics, and learning them alone won’t help. But it can help place the candidates at unique jobs like conducting predictive and prescriptive analysis on routine.

 

Problem Solving

The whole purpose of using big data in business is to identify internal issues and solve them with technology. Therefore, being thorough with tools and techniques alone won’t help. You have to understand the business perspectives and problems that need immediate attention. Implementation of big data techniques with creativity and problem-solving skill will help your organization greatly.

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