The volume of data flowing into organizations is on the rise, and exponentially so. Organizations have come to realize that this is a potential source of great insights to guide their future course of action, which is why big data has become very important in recent years.
The big data industry has shown immense growth in recent years, driven by executives across industries realizing the value it can deliver. From healthcare to marketing and technology, scarce is the organization that cannot derive value by sifting through its data. This growth has got a further push from the rise of digital platforms and technologies, facilitating the availability of information that big data professionals at organizations can mine to gauge useful insights.
There are a number of ways in which big data can help organizations, and some of these are listed below:
- Availability of sophisticated data-based analysis
- Developing sophisticated business strategies
- Improving toplines and bottom lines
There is strong demand for skilled professionals.
It follows logically that the demand for skilled big data professionals is rising. However, the growth in job openings far outstrips that in availability of suitable talent. The growth in big data means the demand is likely to stay strong in the foreseeable future.
The gap comes about due to the rapid growth of digital platforms and technologies and the consequent upsurge in data availability. Data storage no longer is a concern, and the focus is now on finding enough skilled people to deal with the challenge of pulling out productive insights from large amounts of complex data. According to Analytics Insight, India will see 1.5 lakh new data science job openings by 2020, an increase of about 62% compared to 2019. About 70% of the present job openings are for data scientists with under five years of work experience.
What career paths are available?
For someone looking to work in the big data industry, the following are the possible roles:
- Data scientist: This refers to someone qualified in data analytics and working to gather data, scrutinize it, and offer workable insights towards improving strategy and operations. Among the big data professionals, a data scientist typically is highly academically oriented, with proficiency in computer programming, mathematics, and statistics. Over time, data scientists have moved beyond working only in academic capacities to working for a range of industries.
According to the US Bureau of Labor Statistics, the following are the tasks handled by a data scientist:
- Number-crunching
- Data review
- Data organization into coherent formats
- Data analysis
- Generating reports with significant trends and insights
Apart from an advanced degree, a data scientist must be proficient in:
- R, SAS, and/or other common analytics platforms
- Statistical analysis and data logging
- Using tools such as HighCharts and AmCharts
- Calculus and algebra
- Predictive analytics developer: A more specific role, this requires using insights gleaned from data analysis to make predictions that help a company in multiple aspects of its operations, including making business strategies for the future. This domain of analytics is common in marketing, retail, and sales, given that they focus on consumers and their behavior.
- Marketing analytics professional: The key task in this role is to leverage data platforms to evaluate the efficiency of marketing campaigns undertaken by the organization, along with measuring the return on the investment made. Data studied for this role could come in different formats:
- Change in sales of a product after the launch of a new marketing campaign
- Engagement levels derived by new marketing campaigns from consumers online, looking at company websites and social media
- Visualization tool developer: This role looks at the design and construction of platforms for visualizing data. Such tools facilitate more rigorous data analysis by data scientists and analysts. The growth in the big data industry has meant there is a high demand for professionals in this field, and they need a strong background in big data and a background in software development.
Is certification useful?
Getting a big data certification is an excellent career decision by an aspiring professional in this field. A certification is a proof of:
- Seriousness about the job role and career
- Competence with current skills and technologies
- A desire to stay relevant and do well
A big data certification can help a professional looking to enter the field, and it is also helpful for those who want to move up within the field.
