Digitalization is the flavor of the world today, with digital technologies changing business models and providing new opportunities to generate revenue and produce value. Across companies of all sizes and in all verticals, this has meant huge amounts of data flowing in. The implications are two-fold:

• The incoming data needs to be properly segmented and stored

• The data could be analyzed to provide some very valuable strategic insights

For these reasons, big data analytics is most definitely here to stay. Its importance will only grow in the years to come, given that the inflows of data will only keep rising, and companies are always looking to do whatever they can to stay ahead of their competitors. Big data revenues across the world are projected to increase from USD 42 billion in 2018 to USD 103 billion in 2027, at a CAGR of 10.4%.

This also means a big data career could be a very rewarding choice. Salaries are quite impressive, with the median annual salary at USD 116,000 and even the entry-level package at USD 92,000. With more companies realizing the worth of having specialists in big data and analytics in their team, the number of job openings in the field is only going to rise. In fact, 80% of data scientists say there is a shortage of professionals in the field. In the US alone, 2.7 million job postings for data analytics and data science are projected by 2020.

To boost a career in big data and analytics, the following are the key considerations:

Educational requirements

Research suggests the following statistics:

• Data scientists with a bachelor’s degree: 8%

• Data scientists with a master’s degree: 44%

• Data scientists with a PhD: 48%

The above shows that 92% of data scientists have an advanced degree, which points to the usefulness of high academic qualifications for a big data career. There is also the option of taking up a big data certification to add to current qualifications so that potential employers know the candidate is up to pace with the latest tools and techniques and is serious about career growth.

Variety of job roles

There is a variety of roles that professionals play when working in the field of big data analytics. These include the following:

• Data analyst: Drawing insights that directly impact business decisions

• Business intelligence analyst: Use data to understand the position of the company and the trends in the market

• Data visualizer: Creating dashboards and other forms of data presentation to inform management

Being versatile and skilled in more than one domain makes a person more valuable to the organization and more likely to grow faster in the field.

Identifying opportunities within the organization

Look within the company for an opportunity to apply big data analytics. Find sources of data and check if the data is being collected in some repository. Typically, one of the other business processes collects data, which could be mined for insights.

Start with low-hanging fruit. It may not be wise, to begin with, a predictive model; instead, just generate simple insights currently not captured in business reports. Simple metrics could add great value and catch the attention of senior management.

Taking on additional skills

In the course of a big data career, prospects can be boosted greatly by taking on additional skills. The options to consider include the following:

• Data science with Python, R or SAS

• Hadoop and MapReduce

• Real-time processing

• Machine learning and data mining

• NoSQL databases

• Data visualization (Tableau)

• Statistical tools such as R, SAS, SPSS, and MATLAB

Taking on courses and big data certifications gives professionals the edge to stay ahead of others in the field, and the edge to become a highly valued member of a team. It demonstrates initiative and drive, cementing a place as an asset to the company.

Given how recently the field has come up, this is a great time to join this new and vibrant area of technology.

Great thread op. You can hardly see a thing like this in front page.

We are somewhat abusing the word data science in Nigeria. People are missing it up with data Analyst or worst still, data entry. You will see a job ad that wants to pay data scientist or even data analyst 60k Naira. I always laugh. Yet they will be asking for skillset that will make you collect $20k salary somewhere else. Dem no know pass Microsoft Excel.

I just added NoSQL to my skillset during this stay at home. I did MongoDB and currently working on Cassandra... hoping to change job soon.

I am currently analyzing Korea Coronavirus data. NCDC no gree get data. Na number of death, new and existing cases, and discharge you go see for their site.