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The ABCs of Big Data

In today’s digital world, Big Data reigns supreme. Here’s all you
need to know about one of the fastest growing fields of the decade.

Big Data is opening the door to massive opportunities in the world of work.
Between 2011 and 2017, the demand for big data analysts grew by a record 3977%, and the market itself is expected to reach an impressive $58.9 billion by 2020.
Spread across every industry and every function, big data is the hot job sector of the century. In fact, much like software development in the early 90s, the big data sector is growing faster than companies can recruit qualified individuals.
Here’s a quick rundown of the things you need to know if you want a lucrative career in Big Data.

What is Big Data?

Big Data is the data created by sources like the internet and social media. These complex sets of data need to be stored, processed and analysed using particular tools and methods.

The rising popularity of big data can be attributed to its immense potential. It can help businesses with product management, operational efficiency, customer experience and even machine learning.

What are the must-have core skills in Big Data?

We have identified seven core skills essential to succeeding in Big Data:

• Programming
This is the bread-and-butter skill for anyone who wants to work in the Big Data world. Get up to speed on your statistical programming languages (like Python and R), and know your SQL inside out (SQL stands for Search Query Language and is used to manipulate the data from databases).

• Statistics
Understanding how statistics work is essential. Selecting the appropriate methodology is something that is covered across most disciplines at university, including the social sciences. This is one of those ‘transferable skills’ but it really comes to the fore in big data analytics, where small alterations in an approach can make all the difference.

• Multi-variable calculus and linear algebra
While there might be in-built programs to do this part of the job for you, skills in this area can nonetheless give you an advantage over other candidates. This is especially true for businesses whose product is defined by data (think, banking and financial services). This skill will also appeal to companies who are looking for an in-house developer to set them ahead of the curve.

• Data wrangling
Spotting holes or gaps in the data is part of any job in big data, so this one is an absolute must-have for all analysts.

• Data visualisation and communication skills
Combining expertise in data analysis with excellent communication skills is a huge advantage in this field. Companies will rely on you to interpret their data for them, especially if they are using big data for the first time. Remember to brush up on the latest programmes for data plotting (e.g. matplotlib or ggplot).

• Problem-solving
It is not enough to just plot the data. Go the extra mile and learn to analyse and interpret it. Doing so will help your company plug gaps and explore countless opportunities for growth and innovation.

• Machine learning
It is not necessary to learn every single detail of machine learning, but even a general overview of it will stand you in good stead in a data-reliant company (like Netflix or Uber).

What are the main job positions in Big Data?

The classic, one-size-fits-all term for someone who works in Big Data used to be ‘data scientist’. In recent years, however, people have slowly begun to refine their understanding of the niche roles within the sector. From data scientists to data engineers, architects to analysts, the opportunities are as vast as the data itself.

What’s more, people are increasingly opting to specialise within certain domains. While a lot of the learning for such roles is done on the job, it certainly helps to carve your niche out early and predict the likely changes in trends.

The core skills, however, remain the same.

Where to start your Big Data career

Universities are beginning to understand the potential in Big Data and are creating specialist courses — especially at the Master’s level — that include big data analytics, data sciences and statistics.

If you’re not sure of your specialization, explore the key skills needed, look for courses that will teach you these and then, map your own path. Some undergraduate options that will give you a good foundation are Maths, Statistics, Computer Science and Engineering.

Don’t forget that programs and software change over time, and also vary from job-to-job. Keep yourself up-to-date on these, as well as the transferable skills that you will come across.

Constant learning and application is key to getting ahead in this field.

Date added
22.11.2019

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