By 2024, the world’s enterprise servers are set to annually process the digital equivalent of a pile of books that extends to more than 4.37 light-years to Alpha Centauri, our closest neighbouring star system in the Milky Way Galaxy. And according to the authors of this report published by the UC San Diego, some of the information is quickly discarded, and is transient. But the bulk of the data (literally the iceberg below the water) needs to be sorted, interpreted, and analysed.
Big Data and Analytics are THE hot skills in demand today. And it is easy to see why.
What’s the buzz around Big Data?
According to the International Data Corporation (IDC), the big data market is poised to grow from $130.1 billion in 2016 to more than $203 billion in 2020, at a compound annual growth rate (CAGR) of 11.7%. 84 percent of mid-market businesses in Australia has taken the Big Data route by deploying appropriate solutions. To be able to be sustainable and efficient, businesses are looking at leveraging the power of Big Data as an important item on their corporate agenda.
According to several industry experts, the Big Data sector has recorded six times faster growth than the average growth rate of IT industry in a span of just two years. Based on its current size and expected rate of evolution, one can certainly say that it is one of the fastest growing career choices in IT sector.
The fact that IBM advertised close to 2300 jobs requiring Big Data-related expertise such as data warehousing and Python programming skills stands testimony to how Big Data is driving change in the direction of re-aligning existing skillsets to create several new job opportunities.
What do Big Data professionals bring to the table?
The value of data lies in the hands of those who analyse it. A McKinsey Global Institute study states that Big Data Analytics form the core of meaningful insights that organisations seek. Therefore, the contribution that Big Data professionals make in this scenario is quite significant. Equipped with the right analytical skills, Big Data professionals add immense business value to an organisation by identifying opportunities and insights from unstructured and non-traditional data sources. For instance, Big Data experts at Nissan had come up with a host of localised websites designed to help consumers determine which Nissan product is best for them. A step beyond just simply measuring conversions, Big Data professionals were able to provide customers with a comprehensive insight that delved into the car types, models and colours.
What skills are mainstream IT professionals looking to develop?
To be able to sustain in the revolution that is Big Data Analytics, IT professionals should look at focusing on a domain and develop their expertise around that. Here are some quick pointers if you are looking at making the best use of the Big Data revolution.
- Learn how to code: Invest in learning advanced analytics tools and methodologies, such as data mining, modelling, and advanced coding and programming. If your interest is leaning towards learning a programming language, Python would be your best bet for starters.
- Develop an aptitude for quants: Building a strong foundation in numerical analysis is considered as a starting point for a successful career in Big Data Analytics. Concepts relating to numerical and statistical analysis form the core quantitative skills for every successful big data analyst. Being efficient in this paves the way for grasping concepts such as neural networks and machine learning.
- Be versatile: Increase your familiarity with a range of technologies, tools, platforms, hardware and software. At the enterprise level, SPSS, Cognos, SAS, MATLAB are important to learn as are Python, Scala, Linux, Hadoop and HIVE.
- Expand your repertoire: Work on developing your skills in the direction of domain expertise. This could come in handy in all your interactions with different stakeholders. This would also add value to the insights that you derive from analysing scores of raw data.
It is safe to conclude that the burgeoning demand for qualified data professionals is also just the tip of the iceberg. Data analytics professionals who are well versed with SQL, Hadoop, Python, Java, R and Hive are setting themselves up for a pretty interesting job market. Due to their niche specialisation, they can explore a wide range of roles ranging from Data Engineer to Business Analyst and Analytics Functional Expert to Solution Architect.
