Why You Should Learn Data Analytics

By BrainStation May 8, 2019

With each passing year, data becomes a bigger part of our lives and a bigger priority for businesses across all sectors.

The International Data Corporation recently released its 2019 update to the Worldwide Semiannual Big Data and Analytics Spending Guide, showing that worldwide revenues for big data and business analytics solutions were forecast to reach $189.1 billion this year, a 12 percent increase from 2018. The report also concluded that this high rate of growth was likely to continue, with worldwide data and business analytics revenue reaching $274.3 billion by 2022.

“Digital transformation is a key driver of big data and business analytics spending with executive-level initiatives resulting in deep assessments of current business practices and demands for better, faster and more comprehensive access to data and related analytics and insights,” said Dan Vesset, Group Vice-President of Analytics and Information Management at IDC.

“Enterprises are rearchitecting to meet these demands and investing in modern technology that will enable them to innovate and remain competitive. Big data and business analytics solutions are at the heart of many of these investments.”

So, what does that mean for you? Data analytics is a field ripe with opportunity. Here are a few reasons why there has never been a better time to learn data analytics.


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Companies are Investing More Than Ever in Analytics

In recent years, companies across all industries have made big commitments to big data.

According to a study by Dresner Advisory Services, big data adoption in enterprises surged from 17 percent in 2015 to 59 percent in 2018. And if you think that it’s only traditional “tech” companies investing in big data, think again. Dresner’s study found that big-data analytics adoption was highest in the telecommunications (95 percent adoption), insurance (83 percent), and advertising (77 percent) industries, followed by financial services (71 percent), healthcare (64 percent), and technology (58 percent).

Breaking down how organizations use data analytics, the study found that the adoption rate was highest in areas including research and development (75 percent) and operations (63 percent), but marketing and sales, and IT departments also reported plans to build out their analytics.

Similarly, the industries lagging behind in big data analytics adoption – including education, government, and manufacturing – all pledged to increase their big data analytics activity in the future.

Indeed, some industries still seem poised to be transformed entirely by big data analytics.

A recent McKinsey report forecast how digital analytics would change marketing – with the promise of data-activated, one-to-one marketing interactions – operations and manufacturing especially.

“Business is now in the midst of the most significant disruption in decades,” read the report. “This epochal transformation has been driven largely by technological changes – big data and advanced analytics, additive manufacturing, the Internet of Things, robotics, and artificial intelligence – collectively described as the fourth industrial revolution.

“Arriving at dizzying speed, its consequences are already evident across sectors: competition is intensifying not just within industries but between them.”

Even with the rapid adoption rates across industries, studies have shown that most still aren’t investing enough in big data analytics. Another McKinsey study found that if the U.S. healthcare industry were to use big data effectively to drive efficiency and quality, the sector could create more than $300 billion in value, while a retailer using big data to its fullest potential could increase its operating margin by more than 60 percent.

“The use of big data will become a key basis of competition and growth for individual firms,” the study read. “From the standpoint of competitiveness and the potential capture of value, all companies need to take big data seriously. In most industries, established competitors and new entrants alike will leverage data-driven strategies to innovate, compete, and capture value from deep and up-to-real-time information.”

Other Career Switchers Have Proven it’s Possible

If you’re convinced that your skillset or experience wouldn’t lend itself to data analytics – or that you’re too far behind to start now – you should take comfort in the abundance of career-switchers who have thrived after picking up data skills.

According to BrainStation’s 2019 Digital Skills Survey, 79 percent of respondents did not begin their career in data, and 65 percent had been working in the field for only five years or less.

It’s worth pointing out that those data professionals do tend to be lifelong learners. BrainStation’s survey found that 72 percent had participated in online courses, 68 percent in workshops, seminars or conferences, and 63 percent had taken in-person courses relating to data.

It Can Make You More Valuable (Even If You Don’t Have “Data” in Your Title)

Although there’s an obvious need for Data Analysts, it’s increasingly common to expect data skills in other roles as well.

For those working in marketing, communications, social media, journalism, or content management, an understanding of data is increasingly becoming not just an asset but a necessity for digital strategies. As we mentioned earlier, there’s really no end to the number of industries increasing their focus on data, including aviation, retail, and even the public sector.

Moreover, many organizations have a foundational overall problem with data literacy. BrainStation’s survey found that 52 percent of data respondents rated the data literacy in their organizations as “basic,” while only 17.1 percent replied that their organization’s data literacy was either advanced or expert.

There’s a Shortage of Data Professionals

According to a report from McKinsey, the United States faces a shortage of 140,000-190,000 people with analytical skills, as well as 1.5 million managers and analysts who understand how to use data analysis to drive decision-making.

In its 2017 report The Quant Crunch: How the Demand for Data Science Skills is Disrupting the Job Market, IBM predicted that the number of jobs for U.S. data professionals would grow from 364,000 to 2,720,000 by 2020. And IBM added that if that nearly every one of those 2.8 million “analytically savvy” workers who would fill that gap would have to change jobs to do so.

Salaries have, of course, risen with demand. The average salary for a Data Analyst in the United States according to Indeed is $68,523, rising to $86,500 among Senior Data Analysts.

In certain industries, even junior Data Analysts are richly rewarded. According to a study by Springboard, Data Analysts in natural resources and mining can expect salaries north of $100,000, those working in professional, scientific and technical services they can earn $90,000 on average, and those Analysts employed in the finance and insurance sector average around $90,000 as well, with almost 400,000 jobs.

Specific competencies can nudge those salaries even higher. According to IBM’s report, Data Analytics professionals with MapReduce expertise bring home an average annual income of $115,907. Similarly, professionals with experience using Apache Pig, Hive, and Hadoop are in the market for jobs that average over $110,000 per year.

The Future Is Bright

As serious as the projected talent shortage in data is, those estimates might even be conservative when you consider how technological innovation has the potential to unlock further opportunities in the data field.

BrainStation’s survey found that roughly 80 percent of data professionals believe Machine Learning and AI would have an impact in the next five years, while blockchain and internet-of-things technology (which Gartner expects to reach 20.4 billion devices by 2020) are also expected to take on greater prominence. And the global augmented analytics market is expected to grow from $4.8 billion to $18.4 billion by 2023.

By building competency in data now, you could be well-positioned to take advantage of an industry that seems poised to continue its rapid growth.


Learn data skills to boost your career – from home!

BrainStation offers Online Live Certificate Courses in data science, data analytics, machine learning, and python programming. Attend live classes and interact with Instructors and peers from anywhere in the world.

Speak to a Learning Advisor