In the world we live in today, every mouse click generates data. Now imagine the amount of data every individual across the globe is creating, every day – nearly incomprehensible! Thanks to Big Data technologies, we can make sense of this enormous data pool and use it to our advantage. According to a recent report, by 2021, the Big Data market is expected to grow from USD 28.65 billion (as of 2016) to USD 66.79 billion at a CAGR of 18.45%.
In essence, Big Data refers to extremely massive datasets that contain structured, semi-structured, as well as unstructured data that are beyond the processing capacities of traditional data processing and BI tools. This is where Big Data tools come in handy to process and analyze vast amounts of data, thereby revealing valuable patterns, trends, and associations that can be beneficial for companies across the various sectors of the industry.
Why Learn Big Data?
Big Data is the source of all the answers. Big Data has opened the door to new possibilities. Because of Big Data, organizations can find solutions and answers to complex issues they thought did not even exist. By collecting, processing, analyzing, and interpreting massive amounts of raw data, organizations can gain a more comprehensive understanding of their industry, their products/services, the needs and preferences of the target audience, and their biggest competitors. Furthermore, Big Data technologies like as Hadoop, Spark, and cloud-based analytics also facilitate cost-reduction, enhance business efficiency, and boost customer satisfaction through a better understanding of data.
Here are seven reasons why you should invest your time in learning Big Data:
1. The Big Data market is growing exponentially.
Like we mentioned before, the global Big Data market is growing at an unprecedented pace. This is mainly due to the increasing penetration of smartphones, smart devices and IoT, and better and increasing Internet access around the world. The Big Data Analytics market in India is expected to grow eight times its size by 2025, reaching USD 16 billion from USD 2 billion (as of 2016). NASSCOM targets to make our country one among the top 3 Big Data Analytics markets.
2. Big Data adoption has increased manifold.
By now, companies across the various sectors of the industry have come to realize that without Big Data they cannot keep pace in the competitive market. Anyone who isn’t using Big Data is missing out on an ocean of opportunities. Thus, more and more organizations are adopting Big Data technologies and cloud-based analytics to gain a competitive edge in the market.
3. Big Data is everywhere.
Yes, Big Data is omnipresent, starting from the IT, business, and e-commerce sectors, Big Data has now made its way into healthcare, education, banking & finance, insurance, retail & manufacturing, and even governance. Big Data is used by all these sectors for predictive analysis, offering customized services, producing innovative products, boosting customer satisfaction, and so much more.
4. Diverse and increasing job opportunities.
Since more companies are joining the Big Data bandwagon, they are always on the lookout for skilled professionals in Big Data. Specialization in Big Data has given birth to numerous versatile career opportunities such as Big Data Engineer, Big Data Analyst, Big Data Architect, Business Intelligence Analyst, Data Modeler, Data Scientist, Database Administrator, to name a few. The fact that Big Data is a hot topic in the industry makes these job roles highly lucrative and promising in the present scenario.
5. Not enough skilled and trained professionals in Big Data.
While it is true that employment opportunities in Big Data are spurring, there is a significant gap between the demand and supply of well-trained and skilled professionals in this domain. Amit Aggarwal, the Chief Executive of NASSCOM’s IT-ITES Sector Skills Council, maintains his statement:
“There is an urgent need to re-skill about 50 percent of India’s IT workforce, as demand for it in new technologies remains unmet…Going forward, the industry will face a shortage of 2,30,000 skilled techies as jobs in AI and Big Data are estimated to be 7,80,000 by 2021.”
This is one of the primary reasons why potential recruiters in the industry highly value Big Data skills.
6. Higher salaries for skilled Big Data professionals.
The shortage of skilled professionals in Big Data drives companies to pay higher packages for candidates who have the right skillset for it. In India, a person holding a Master’s degree in Big Data/Data Science/Data Analytics or other related fields can get a starting salary of around Rs. 4-10 LPA, while those with 3-6 years of experience in the domain can make anywhere between Rs. 10-20 LPA. Professionals having 6-10 years of industry experience can make Rs. 15-30 LPA, and those with over 15 years of experience can earn as high as Rs 1,00,00,000 LPA.
7. Big Data offers plenty of opportunities for freelance jobs.
Today, a large percentage of the younger population does not want to stay rooted with just one employer or organization. They are continually looking for opportunities to expand their skill set as well as sources of income. Upskilling to Big Data allows you to work as a well-paid freelancer for many companies, particularly IT-based ones. As a freelancer, you can work from anywhere, anytime.
How to Kickstart a Career in Big Data?
The best way to kickstart a career in Big Data is to enroll in a Big Data Hadoop Certification Course.
While a background in Information Technology/Computer Science/Statistics is preferred for Big Data jobs, these do not dig in deep into the Big Data domain. Taking up a Big Data course will help you acquire all the skills relevant to the field in a step-by-step approach. You will start by honing your coding (R, Python, Ruby, C++, Java, and Scala) skills along with your Mathematical and Statistical skills (Linear Algebra, Multivariable Calculus, Probability Distributions, Dimensionality Reduction, Hypothesis Testing, Bayesian Statistics, etc.).
Big Data courses also teach you how to work with various computational frameworks (Excel, SQL, Hadoop, MapReduce, Spark, Storm, SAS, etc.) and even with relational and non-relational databases (MySQL, NoSQL, HDFS, Oracle, DB2, MongoDB, Cassandra, etc.). Another great advantage of taking up a Big Data course is that they teach you how to develop different soft skills (communication, people management, team collaboration, etc.), which helps you become a valuable asset in a company.
