Big Data is the buzzword these days. An observable trend in the IT industry has been the workforce moving from coding to data science and analytics. Everybody wants a bite of the big fish, but do we know how to master the art of dealing with big data? What do we need to learn to become big data experts?
The efficient application and mastery of big data stands effectively on four pillars:
1. Knowledge of the technology landscape
There is no one go-to solution when handling Big Data, with numerous technologies taking centre stage in this landscape. It is vital for a Big Data analyst and a data scientist to be able to comprehend what the data says and map a business solution accordingly. One needs to know the infrastructure and how to select the right tools for storing, processing and analysing big data.
The Big Data industry is still at a very nascent stage, both in India and worldwide. On the heels of a realisation that data is a key element of business processes and decisions, we now have a high level view of the data and analytics sector. The crucial thing here is to know what the tools are there and how they fit into the bigger picture.
A big data expert needs to know how business processes function and when and how big data and related technologies can be leveraged to optimize them. It is not enough just to analyse data, but to know how this information can be relayed back to decision makers so as to assist in overall growth of a product or service. It is all about understanding market trends and being able to bridge the supply and demand gap with the use of data.
2. Knowledge of data analysis techniques pertinent to big data
Data analysis techniques are abundant, and as a big data expert, one is expected to know how each of these techniques functions and where it would be most beneficial to apply them when dealing with big data. A solid understanding of real-world techniques and implementations that create business value, gives a data professional the necessary edge.
3. Programming knowledge to manage processes and manipulate data
While programming knowledge and skill are not mandatory, it pays for a big data professional to have them, as the tools and processes for analysing big data are software-based. Without adequate programming skills, the data itself is pretty useless. Numerous tools such as SAS, R, SPSS, and Python, among others, are all software tools that make dealing with such huge amounts of data easy. Knowing how to assemble them (write code), makes it that much easier to cope with any programmatic glitches that might crop up.
Also, companies these days are downsizing their IT departments and are on the lookout for Big Data professionals who are also comfortable with coding.
4. Understanding common business problems that need big data solutions
Recent trends have shown that data can solve many major business problems, help with decision-making and ensure that processes are well-organized and optimized. A big data professional must definitely know and understand the kinds of routine business problems that call for big data interventions. Once all the data has been processed and analysed, it’s the actionable insights extracted from them that enable strategic business decision-making and affect a company’s growth and scaling.
Big data analysts are at the vanguard of the journey towards an ever more data-centric world. Being powerful intellectual resources, companies are going the extra mile to hire and retain them. You too can come on board, and take this journey with our Big Data Specialization course.