Traditional data analysis fails to cope with the advent of Big Data which is essentially huge data, both structured and unstructured. Much more is needed than being able to navigate relational database management systems and draw insights using statistical algorithms.

The good news is that the analytics part remains the same whether you are dealing with small datasets, large datasets or even unstructured datasets. What is needed the most in Big Data is the ability to draw relevant information from the humongous amounts of data being processed every minute. This requires technology to join hands with traditional analytics.

Let us now look at some of the key Big Data skills needed for being an expert Big Data Analyst.

  1. Programming
  2. Data Warehousing
  3. Computational frameworks
  4. Quantitative Aptitude and Statistics
  5. Business Knowledge
  6. Data Visualization

1. Programming

While traditional Data Analysts might be able to get away without being a full-fledged programmer, a Big Data Analyst needs to be very comfortable with coding. One of the main reasons for programming skills required for Data Analysts is that Big Data is still in an evolution phase. Not many standard processes are set around the large complex datasets a Big Data Analyst has to deal with. A lot of customization is required on a daily basis to deal with unstructured data.

You must be wondering which programming languages fall under Data Analyst requirements? To answer your question, languages like R, Python, Java, C++, Ruby, SQL, Hive, SAS, SPSS, MATLAB, Weka, Julia, and Scala. As you can not allow, not knowing a language to be a barrier between your dream of becoming a Big Data Scientist. At the minimum, one needs to learn R, Python, and Java. While working, you may end up using various tools. Programming Language is only a tool, and the more tools you have in your kitty, the merrier it is.

2. Data Warehousing

Data warehousing is one of the must-have big data skills required to become an expert Big Data Analyst. Experience with relational and non-relational database systems is a must. While the examples of the non-relational database include Mysql, Oracle, DB2, at the same time, NoSql, Hbase, HDFS, MongoDB, CouchDB, Cassandra, Teradata are a few of the examples of the non-relational database.

3. Computational frameworks

A good understanding and familiarity with frameworks such as Apache Spark, Apache Storm, Apache Samza, Apache Flink, along with the classics MapReduce and Hadoop, is one of the essential skills required for a Data Analyst. These technologies help in Big Data processing which can be streamed to a great extent.

4. Quantitative Aptitude and Statistics

While the processing of Big Data requires great use of technology, fundamental to any analysis of data is good knowledge of statistics and linear algebra. Statistics is a basic building block of data science. Understanding core concepts like summary statistics, probability distribution, random variables, and hypothesis testing are important data analyst skills if you wish to become a proficient Data Scientist of any genre.

5.  Business Knowledge

To keep the analysis focused, to validate, sort, relate, evaluate the data, one of the most critical Big Data skills of any Big Data Scientist is to have a good knowledge of the domain one is working on. In fact, the reason Big Data Analysts are so much in demand is that it’s very rare to find professionals who have a thorough understanding of technical aspects, statistics, and business. There are analysts good in business and statistics but not in programming. There are expert programmers without the know-how of how to put the programs in the context of the business goal.

6. Data Visualization

It is important that you can tell an interesting story with data to get your point across and get your audience involved. You’ll have difficulty getting through to others if your insights are not easily and efficiently found. For this purpose, Data Visualization may drastically affect the impact of your data. In order to present their results in a transparent and concise way, analysts use high-quality graphs and charts.

To kickstart your data analysis career, it is important to know what Big Data skills you need to break into analytics and start working with data. Companies are searching for professionals with these in-demand, short-in-supply Data Analyst skills. Improving your Big Data skills today means more opportunities and more lucrative salary packages for your future.

Let’s take a look at how you can hone your Data Analyst skills.

Developing Your Big Data Skills

There are several ways you can learn these six Big Data skills to help you achieve your goal if you are determined to make this transition to an analytics profession. The way you decide to develop these Data Analyst skills depends on your current experience, time, money, and personal goals.

It can be helpful to use books and other free tools for aspiring Data Analysts when beginning their journey. This will allow novices to get to know the terminology and provide a good base for future growth. However, those who wish to transition more smoothly to the field should seek opportunities to acquire the Big Data skills required to become an expert Data Analyst.

Formal education is one of the most effective ways of doing this. If you want to study online, bootcamps or analytics certification programs are available to help you upskill and grow in this highly competitive area.

Parth Cholera, AGM – Network Automation & Process/System/Business Analyst at Vodafone Idea Limited, like many other professionals, has chosen to upskill his Data Analyst skills and transform his career with Jigsaw Academy’s Postgraduate Program in Data Science and Machine Learning (PGPDM), in association with The University of Chicago Graham School. “With the help of this course and a thorough understanding of the current challenges, I was able to design and develop innovative solutions for a better Operational and Business model using AI/ML/Advanced analytics techniques within Telecom Network Domain,” says Parth, sharing his thoughts about the program. You can read more about Parth’s experience by clicking here.


In this article, we’ve listed 6 must-have Big Data skills that will guide you if you’re beginning your research and are wondering how to make the transition to a career in the field of Big Data and build a promising career. 

If you wish to navigate your career towards success like Parth, then Jigsaw Academy’s Data Science programs will surely help you. Recognized as the No.1 institute for Data Science training in India over the last multiple years, Jigsaw Academy is adept at offering upskilling opportunities to fresh graduates and professionals in Data Science and emerging technologies. To know more, visit our website.

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