It’s not hard to see that today’s tech market is dominated in big data and cloud computing. These two areas often go hand-in-hand and often see a crossover of skill sets.
This is a quick guide to the most important big-data skills you need to have on your resume if you want to start your career in AWS.
Programming languages
Machine learning and Artificial Intelligence
Quantitative analysis
Data mining
Problem-solving
SQL and NoSQL databases
Data structure and algorithms
Data visualization and interpretation
The AWS Big Data Certification

The most sought-after big data skills
Programming languages: Python, Java, C++ are three programming languages that are worth your time and money.
Although it is not possible or necessary to know every programming language, the more relevant the languages you know, the better your career prospects.
According to the AWS Salary Survey, Python, Java and JavaScript are the top three programming languages that will be most in demand in 2020.
Cloud professionals also named C# and Go, Golang as the most important languages to have in your toolbox for this year.
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Java is the language of choice for open-source big data offerings. If you are familiar with Java, you will already have the technical mindset required to tackle Hadoop For Spark.
Spark uses Scala because Scala was designed with functional programming in mind and immutability, making it compatible both with Spark’s RDDs and Spark’s APIs.
Python is a popular language for text analytics. It also provides a solid foundation for big-data support.
You will likely be involved in scripting if you develop or work with big data platforms. Python is one of the best options.

Machine learning and AI. With the digital skills gap growing, organizations around the world are in an ever-increasing race to hire big data professionals with machine and AI skills. Neural networks, reinforcement, adversarial, logistic regression, supervised, machine learning – the list goes on.
Your contribution is more valuable to progressive tech-focused employers today than it is your salary.

Quantitative analysisQuantitative analytics is an integral part of daily life in big data because it all comes down to numbers.
Strong math and statistics skills will make you a strong hire. You will also be able to use powerful tools such as SPSS and R to your advantage.
Having a background in mathematics–especially calculus and linear algebra–will give you a great foundation for understanding the probability, statistics, and algorithms involved in a big data job.

Data miningTechnological advances over the past five years have taken data mining up to new heights.
The tech landscape is in high demand for big data professionals with data mining experience. So invest some time in building your data mining toolbox with industry favorites like Rapid Miner and KNIME.

Problem-solvingHaving a naturally analytical mind will take you a long way in this line of work. It doesn’t matter if you are a naturally gifted analyst, it will take constant practice to improve your skills and become a big-data bigshot.
There are many ways to sharpen your analytical skills, such as solving puzzles, playing Chess, and enjoying videogames that challenge you in problem-solving.
Consistency is the key.

SQL and NoSQL databasesSQL are the foundation of big data and are central to Hadoop Scala warehouses.
Distributed NoSQL databases such as MongoDB can be quickly replaced.