10 Must-Have Skills for Big Data Experts in 2019

10 Must-Have Skills for Big Data Experts in 2019

Big Data is everywhere and has become essential not just in the IT industry, but ranges across many industries.

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Big Data is everywhere and has become essential not just in the IT industry, but ranges across many industries. There is hardly any sector that cannot benefit from big data, and this explains why there is a big demand for qualified big data experts to help drive success

Why Big Data is in Demand

There are numerous websites generating data and information at a high rate.  This would include the likes of social media, and online activity logs amongst others. This poses the challenge of extracting information from the huge amount of data generated. This is because organisations need to process and efficiently use this data for building strategy, making decisions and cutting costs at an international level.      

Huge skills gap

Big data experts with an adequate skillset are in short supply compared to the huge demand. Companies have experienced significant skill gaps between their ideal big data experts and what they have at their disposal. Companies in demand of Big Data skills include the IT industry, finance and insurance sectors, professional, scientific and technical services, and retail trade.

Higher Paychecks than regular IT skills

The salaries of professionals with Big Data skills are approximately 40% higher than normal IT skills. According to a recent Forbes report a big data professional earns a median average salary of 124,000 dollars. According to another forecast the market for big data will be worth USD 46 billion by the end of 2018.

Below are some of the must-have skills for big data experts.

Know Apache Hadoop

Apache Hadoop is a powerful big data platform which requires adequately skilled big data professionals to handle the core components. As an open source project, it allows for rapid processing insights into large volumes of both structured and unstructured data. Components like Hive, HDFS, Pig MapReduce and HBase are in high demand. Your knowledge of how to install, configure, maintain and secure Hadoop are essential to your big data toolbox of marketable qualifications.

Be savvy at Apache Spark

Spark is a quicker alternative for complex technologies like MapReplace. Although not as popular as Hadoop, its in-memory stack has increasingly become a paying job. Apache Spark is considered complex and poses a challenge for a number of analysts. Therefore, becoming savvy with Apache Spark opens job opportunities and a career advancement path.

Have an analytical and Problem-Solving skill

It is not enough to master all the tools and technologies in the big data field, having an analytical mind and problem-solving outlook will definitely make you a pro. According to a big data expert at Synapse search, “The internet is noisy and cluttered and it’s also changing on a daily basis, per hour, and per second. The digital market is competitive and it is becoming hard to connect with customers at the right time when they are searching for your business, services and products online.”

To thrive in the big data field, you will need to implement an analytical and problem-solving skill and you can also display an ability to learn, unlearn and relearn.

Be an expert of NoSQL database

Professionals who are experts of NoSQL can find job opportunities everywhere. Scale-out NoSQL databases like Couchbase and MongoDB, are fast replacing the traditional SQL like IBM DB2 and Oracle. NoSQL databases are normally the source of data crunched in Hadoop, on the web and via mobile apps.   

Know Data Visualisation tools

Data visualisation tools such as Tableau and QlikView, basically carry out data analysis to derive important insights from large datasets. A data expert will need to develop an ability to interpret data by visualising it. Being familiar with the business domain can help you understand how to best analyze the data.

Get experience in programming languages

To stand out and have a competitive edge over others in the industry, you need to know how to code and conduct numerical and statistical analysis with huge data sets. General purpose languages such as Java, Scala, Python and C, will give you an edge over programmers whose skills are still stuck at analytics. You don’t necessarily have to learn every programming language available, but you do have to learn a substantial portion thoroughly. However, the more you know, the better your career.   

Master Data Mining

Data mining is one of the hottest big data skills in the IT world today. You can command large salaries if you can master data mining tools such as Rapid Miner, KNIME and Apache Mahout.

Be proficient at Quantitative Analysis

A solid quantitative background is a significant part of a big data career. A good handle on mathematics, particularly calculus and linear algebra, quantitative reasoning, as well as a degree in statistics are an important part of big data, as it includes numbers. To broaden your proficiency, you can add a knowledge of statistical tools like SAS, R, SPSS, Matlab, or Stata.  

Have SQL prowess

SQL is a data centered language that is essential in the big data field. Having proficiency with the Structured Query Language will be highly beneficial while working on big data technological tools such as NoSQL. SQL is also important for the next generation Hadoop-scale data warehouses.

Develop your ability to use Machine Learning

Machine learning is an AI technology that controls big data analytics by learning rules repeatedly in order to spot anomalies and patterns. It is one of the hottest big data fields with a short supply of experts who can successfully carry out a prescriptive and predictive analysis. Professionals with an adept ability to use machine learning are highly paid.

Tips for improving your Big Data skills

    1. Balance your skills with an ironclad determination and a curiosity to know more and never stop learning. It is imperative for you to know that you cannot become an expert in two or three years regardless of how consistently you study or train.
    2. Be ready to develop yourself by taking online courses and obtaining certifications for learning technologies, and do this in conjunction with your studies or present job. Also, make a habit of studying podcasts, reading books or listening to audio books.
  • You can gain hands-on experience at a company, in order to develop your Big Data skills. This is why it is important to look for an employer who is interested in your professional development and one who creates the opportunity for professional development. Alternatively, you can learn from your peers at work who have more experience in the field you desire.
  • You have to keep yourself updated about the new technological and methodological solutions required to analyse big data.
  • It is vital to know how to interpret and determine the quality of your data.
  • You need to know and familiarise yourself with multiple technologies in order to be a skilled data professional. However, some require more attention than others. You may have to carry out research to know the basic tools in demand.

Conclusion

Being hired in the big data field, largely depends on your data analysis competency and your ability to resolve issues logically. Developing a single skill is not enough, so learn the required skills to stay relevant in the field.