Big Data is the all information generated by machines, humans and organisations online. If used properly it can generate valuable insights for better decision-making and has quickly made data science a rapid growth industry worth billions of dollars.
The internet came from humble beginnings, ARPANET was the first computer network and with only two computers connected to it the system crashed when they tried to type ‘LOGIN’. In fact, it crashed after the first two letters!
That was 1969, and 50 years later the average person is producing huge amounts of digital information through things like internet searches, online purchases, sending emails, and using social media.
You might not realise it, but all this information is being stored on servers, which might make you wonder, ‘Who really cares whether you watch a YouTube video or buy music online?’ Corporations and governments, that’s who, and Big Data is what makes it possible for these entities to access this information and use it.
How Big Data is used
If you’ve ever bought anything online, you’ve probably seen the ‘You may also be interested in…’ message. Those messages are generated by algorithms that access Big Data to find out what you’ve liked, what you’ve previously bought and how long you’ve looked at it.
Big Data is about more than just discounts from your favourite e-retailers. As well as a commercial tool, Big Data can be used for social good in things like crime prevention. Data scientists work with police forces to develop crime prediction algorithms to help prevent crimes like burglaries, using data to pinpoint places they are likely to occur based on previous activity, so they can be prevented before more take place.
Big Data can also help with fraud detection, particularly in the financial services industry. Big data analytic systems are great at analysing patterns, so can spot inconsistent spending activity, allowing stolen credit cards and fraudulent transactions to be identified, often before the cardholder even notices them.
Growing up watching her father repair computers in China, international student Shuang’s interest in IT was sparked from a young age.
“I began to develop an interest in computers when I was a little girl. It was from watching my father repair computers and write programs. I still remember my initial fascination with my father working with computers and my enjoyment of watching him work on them.”
Now studying a Bachelor of Science with a double major in Internetworking and Network Security and Cyber Security and Forensics at Murdoch, Shuang is looking forward to her future career in the fast-paced technology industry.
“Networks are everywhere right now. To work on the security and effectiveness of them has become more and more important and so I believe that I will get a good job after I graduate from Murdoch.”
The challenges in Big Data
The possibilities for Big Data are really exciting, but they do come with challenges. Like anything relying on data, in order to work well the data used needs to be accurate and relevant to be useful for analysis. Acting on poor quality data provides insights that are at best worthless, or at worst extremely harmful to an organisation.
Using Big Data also relies on keeping up with industry standards and government regulations. This can be tricky, especially when it involves handling and storing sensitive or personal data. Storing sensitive data introduces the possibility for cyberattack. Cybersecurity has quickly risen to become a top-level national security priority across the globe with reports ranking cybersecurity breaches as the single biggest data threat companies face.
Despite the challenges, there’s no denying the opportunities within big data. The data science industry is huge, meaning there will be a growing need for data scientists and data experts with the right skills who can make sense of this data available to us.