Big data is everything in the business environment. Combined with the right technology, big data yields insights that inform important growth decisions and provide an edge over competitors. For this reason, more companies are now adopting big data for fear of missing out, making analytics knowledge one of the most in-demand skills today. This is good news for professionals (and fresh out of college newbies) with skills in big data analytics. Below are the reasons why big data is the right career choice.
Table of Contents
Employment trends show increased demand for big data professionals
Professionals with analytics skills can harness the power of big data to provide tailor-made solutions to problems. This is one of the key reasons why the skill is in demand. To this end, Srikanth Velamakanni, co-founder and CEO of Fractal Analytics states: “In the next few years, the size of the analytics market will evolve to at least one-third of the global IT market from the current one-tenth”. This assertion is confirmed by research and reports from different quarters.
For instance, “The Quant Crunch”, a report by IBM, maintains that by 2020, in the US alone, the number of positions with data or analytics talent will reach 2.72 million. Data-driven decision-makers will continue to be important and will reach 110,000 in the same year.
Figure 1: Analytics landscape projection by IBM
Big data is still growing
There is no shortage of places to apply analytics skills. Companies all over the world cannot escape the reality of big data. In fact, most companies realize all too well the importance that big data has for their bottom lines.
In a study conducted by McKinsey, 50% of respondents said that big data has changed how their sales and marketing functions. This was noted across all industries. Other functions that rely heavily on big data include R&D, supply chain, and workplace management.
Figure 2: Big Data influencing how sales and marketing do business across all industries
Some good companies to start your job search include IBM, SAP, SAS, Amazon, Google, Price Waterhouse Coopers, to mention just a few. Below is an example of a job posting by Amazon.
Big data salaries are among the most competitive
Big data jobs have some of the most competitive pay packages. Anyone, including beginners, can enjoy a lucrative pay from the start of their career. Salaries also vary based on the degree of study.
Figure 4: Big data analytics median salary by job
Companies are willing to spend more, particularly when the professionals being hired are skilled in Hadoop. A survey by Burtch Works shows that Big data professionals earn 30% more than other professionals in the IT field who have the same years’ of experience.
Big data is widely adopted across all industries
Data has existed for centuries; we just did not have the means to harness it. But as technology evolved, computers gained enough processing power to go through large amounts of data with speed. Businesses from all sectors have been quick to take advantage of this development. In fact, most positions require their employees to have analytical capabilities, as shown in the image below.
Figure 5: Data skill sets in demand among most industries
That said, below are industries that rely on big data:
The demand for outcome-based healthcare has revolutionized the healthcare industry world over, by putting data at the core of healthcare provision. Big data allows caregivers to learn as much information as possible about a patient. This, in turn, helps to identify early warning signs of ill health, resulting in less expensive treatment procedures and lesser fatalities. Some notable applications of big data in healthcare include:
Data-driven staffing decisions
Predictive analytics plays a big role in healthcare service provision. For instance, in Paris, France, the Assistance Publique-Hôpitaux de Paris (AP-HP), a group of 44 hospitals, rolled out a big data project that once successful, will ensure smart staffing decisions result in:
- Reduced overcrowding,
- Better handling of emergencies,
- Faster patient turnaround,
- Higher per-bed revenue,
- Reduced overheads such as the purchase of supplies, contingency costs and staff salaries.
The AP-HP hospitals will base their staffing decisions for their shifts on past admission data and will be able to predict staffing by day and hour.
Electronic Health Records (EHRs).
Digital records can tell a lot about patients. A system like Health Connect that is in use in the US and parts of the EU makes it easy for anyone with access to the integrated system to follow a patient’s progress. The system also issues warnings and sends reminders for appointments, prescriptions and lab tests. According to a McKinsey report, the use of EHRs has “improved outcomes in cardiovascular disease and achieved an estimated $1 billion in savings from reduced office visits and lab tests.”
Using wearables to track patient conditions.
Wearables alert doctors when a patient is in dire need of medical care. This allows doctors to prioritize their time and energy accordingly.
Insurance companies are already using data to determine accurate premiums and detect fraudulent claims. Some insurance companies even use apps and devices that allow them to track their customers’ driving habits. For example, Allstate uses the Drivewise program to collect data on risky driving behavior such as speeding and braking information. Those who participate in such programs get lower premium rates.
Such efforts will soon catch up in the rest of the world. However, pricing of tracking devices, insurance products, and data regulation laws continues to pose a challenge in data collection, in countries like India.
Financial Services (Investment and Banking)
Banks and investment firms rely on big data to:
- Offer personalized products and solutions.
- Strengthen security. For instance, data has made it easier for credit card companies to detect and prevent fraud.
- Become efficient and competitive against financial technology startups which are always on the cutting edge of money services.
Defense and aerospace
“War is 90% information. These are the words of Napoleon Bonaparte, and they hold true in this century just as much as they did in his time. But unlike Napoleon’s time, the advantage for today’s military defenses is that information collection and interchange happens in real-or-near-real-time.
Advances in analytics allow us to predict human behavior. This has the following implications for the defense sector:
- Collecting and analyzing intelligence information helps to preempt and foil crime and terror attacks before they happen.
- The lower operational risk for troops on the ground
- Improved accuracy of training programs, both in real and simulation environments.
- Better deployment of troops. Analyzing data collected by autonomous vehicles improves mission planning and prioritization.
“Consumer data will be the biggest differentiator in the next two to three years. Whoever unlocks the reams of data and uses it strategically will win.” Angela Ahrendts, Senior VP of Retail at Apple
Strategic use of consumer data is the biggest advantage of big data for businesses operating in the retail space. Today’s consumer is empowered, thanks to consumer-centric technologies that allow for multichannel-shopping. A customer can go through many touchpoints before finally purchasing. Data on customer activity before buying allows retailers to know the best places to target consumers with adverts encouraging buying.
More so, whether online or brick and mortar, retailers can use big data to predict which products will sell. According to IBM, 62 percent of retailers report that information and data give their businesses a competitive advantage.
While not an industry in itself, recruitment spans across every industry, so it’s worth mentioning here. Big data benefits recruitment efforts in the following ways:
- A wider range of information (drawn from social media, publications, search history, etcetera) gives a more holistic picture of potential candidates.
- It speeds up the recruitment process. It takes roughly 1.5 months to hire. Research findings from glassdoor show that some positions can take roughly 50 days to fill, depending on the industry. During this period, your company will incur direct and indirect costs related to the vacancy. For instance, the stress on the remaining employees may affect their productivity in their areas and indirectly affect your company’s performance. Recruiters who embrace big data have an easier time sifting through data, including doing background checks, and recruiting faster.
- Recruiters can make the right choice with more variables. While vacancy costs are a legitimate concern, a short recruitment period may spell even more disaster in the future. With big data processing tools, you can consider all the variables involved in finding a candidate with the right attributes and skill combination.
Skills required for Big data roles and responsibilities
There is a whole array of Roles that you can take up when you decide to go into big data. The skills you learn should be in line with the specific role you wish to pursue. Below are 3 key roles:
Big Data Hadoop analyst
A big data analyst’s main job is to analyze data and find useful insights. For this role, you need to have the following skills:
- Knowledge of Hive and Pig
- Good command of SQL and Flume
You can fit in this role as a fresher but experience level of up to 5 years is acceptable.
As a Hadoop tester, you will be required to troubleshoot all Hadoop components and either report or fix them. Your job will be to ensure that all applications and processes being designed will work as desired. You will report all positive and negative test cases.
To do this job, you need the following skills:
- Know how to test Junit and MRUnit framework
- Understand Java language for testing MapReduce jobs
- Know Hive and Pig
This job is suitable for Freshers and up to 5 years of experience.
Big Data Architect
This is an advanced role requiring an experience level of 8 years and above. As a Big Data Architect, you will design or customize the entire architecture to work as it should. You will also oversee the deployment of solutions and manage the Hadoop lifecycle.
For this role, you need the following skills:
- Experience delivering on Hadoop platforms like Cloudera or HortonWorks
- Know Hive and Pig
- Understand Hadoop Architecture
- Know Hbase and MapReduce
These roles are by no means exhaustive, but they do give you a picture of what to expect when you sign up for Hadoop.
How to get big data skills
There are online classes available for anyone interested in learning the skills mentioned above. Courses are available for beginners and advanced levels. Below are a few courses:
SimpliLearn’s Big Data Hadoop Certification Training Course. This is an advanced course is tutored by industry experts. Real-life industry projects help to get you prepared for Cloudera’s CCA175 Big Data Certification Exam. You will receive a certificate of completion from SimpliLearn.
Cloudera’s CCA Spark and Hadoop Developer Exam (CCA175). It is a 4-day course taught by industry experts. It is part of the 3-part foundational courses offered by Cloudera. For advanced training, enroll for CCP Data Engineer Exam (DE575) will impart skills necessary to deal with advanced big data scenarios.
Your learning journey doesn’t end with these courses or exams. You must keep up with industry trends, follow influencers in the big data industry and attend tech conferences.
As long as we continue to rely on information, big data will continue to endure. To quote the words of Peter Sondergaard, Senior Vice President at Gartner, “Information is the oil of the 21st century, and analytics is the combustion engine”. Companies will continue to seize upon the growth opportunities presented by big data. As a professional, the onus is on you to use this advantage to grow your career in big data.