Why is Big Data such a Big deal?

New technologies are emerging at a dizzying pace, and everything is becoming more networked, connected and digital.

The Internet of Things (IoT), artificial intelligence (AI), augmented and virtual reality, blockchain, self-driving cars, and drones are all new technologies rapidly changing how we live and work.

In addition to these new technologies, new terms are also emerging along with them. One such term is “Big Data” – a phrase you might have heard in passing but don’t fully understand. Many people don’t know what Big Data means or what it has to do with the future of technology.

What is Big Data?

Big Data is the growing amount of information that people, organisations, and sensors generate. When data is generated, copied, and transmitted over the Internet, the volume of data expands dramatically. And when the information is stored and processed, it is likely to be massively magnified again. The result is that a vast and growing volume of data in the world is waiting to be analysed and used.

Every day, we create close to 2.5 quintillion bytes of data. 90% of the data worldwide today has been created in the last two years. Every corner of the world has some data to offer - climate information is gathered from sensors, social media site posts, digital pictures and videos, transaction records, cell phone GPS, etc.

Big data is often characterised by three V’s: Volume, Variety, and Velocity. Volume refers to the fact that a huge amount of data is being generated. Variety refers to the fact that data comes in many different types, originating from various sources and other formats. Velocity refers to the fact that data is arriving and being generated at an ever-increasing rate.

How Does Big Data Differ from Traditional Data?

Traditional data is structured and collected for specific actions and tasks. Big Data, on the other hand, is unstructured and ordered in bulk for analysis and insights. Traditional data also tends to be processed in a centralised way. Data is stored in databases that a single organisation manages. Big Data is distributed across many different organisations.

Why Is Big Data Important?

Big Data is essential because it gives us insights into every aspect of our lives and our world. It helps us to understand ourselves, our health, our finances, our relationships, and our behaviour. It gives us insights into our climate, environment, and wildlife.

Big Data helps businesses make better decisions and improve their operations. It helps us understand our markets, customers, and supply chains. It helps us better understand our communities, infrastructure, and environment.

According to research, the big data analytics market for software and services is forecast to be worth $103 billion by 2023.

Who’s Using Big Data Right Now?

Big Data is changing nearly every industry and sector.

Here are a few examples:

- Healthcare: Every year, millions of people die from diseases that could have been prevented. Health data has traditionally been challenging to analyse and use.

New technologies and methods of collecting data are helping to make health data easier to study and use. This, in turn, is helping us to understand diseases better and how to prevent them.

Big Data is helping us to understand our bodies, our health, and our behaviours. It’s helping us better understand our diseases, improve treatment, and prevent future illnesses.

- Finance: Big Data helps investors make better decisions. It helps them to understand their customers and their markets better and to forecast future events. ?Big Data also helps us better understand the global economy, which is essential for preventing recessions and financial crises.

- Motor Insurance: DSG, in partnership with Zendrive, offers an IQL (Insurance Qualified Leads) Ecosystem in South Africa which uses Big Data from multiple sensors on the mobile device via the Zendrive SDK to asses the driver behaviour and, therefore risk, and we match insurance companies that are interested in that ‘preferred’ risk.

They understand the customer driving behaviour via a 30-day trial whereby the consumer changes the permission on their phone to allow us to track their driving behaviour.

Post the 30-day trial; we provide the consumer with a personalised quote from the insurance company interested in the risk, which is personalised and cost-effective.

The assessment of the risk upfront yields better results for the consumer and insurer. The profitability per customer improves in the long term when there is a low claim ratio. The personalised service we created, an intelligent ecosystem, produces a new business model for insurance by simply aggregating the data, analysing it, interpreting it, and comparing it to the Insurance risk score produced by actual driving behaviour and will impact the premium price according to preferred risk.

About two years ago, Elon Musk announced that Tesla would start offering its customers a 20 or even 30 per cent discount on regular insurance.

“Our insurance is based on how you actually drive, not how historically people that fit your demographic have driven,” Musk explained.

Now, some in the insurance industry are saying this is the start of a trend of car makers becoming insurers.

The result, they say, could be devastating for traditional insurers, who have nothing like the level of data about their customers that Tesla and other car makers do. It’s the same disadvantage brick-and-mortar retailers have against the likes of Amazon: an often fatal lack of customer information. Technology is changing this for all types of insurance. The ability to collect data about your customers continuously, and to use artificial intelligence to analyse that data, is allowing insurance companies to provide much more accurate, up-to-date risk analyses and to price policies accordingly.

- eCommerce: Data is the new currency. In this business-mature and consumer-first age, data is the driving force behind businesses that can understand their online customers and design products around them. Big data helps e-commerce companies find patterns, trends, and personalisation to better understand their online customers so your products will stand out in today's saturated markets. ?Big data can be used to make recommendations based on “look-alike “ audience data and the likelihood that a person will buy something based on data about customers who have already bought the same product.?This data enrichment at the purchase point may lead to an increase in basket value and wallet share.

- Retail: Retailers use Big Data to understand their customers and their markets better. They also use it to improve their supply chains and their operations.

As new technologies emerge, they will generate even more data. And since they are generating more data, they will require more powerful technologies and tools to analyse it.

This means that the need for Big Data and the technologies that support it will only grow over time. Big Data will continue to transform nearly every industry and impact everyone.

The results of a?global study?commissioned by CA Technologies revealed that the benefits of Big Data clearly outweigh the obstacles in implementing Big Data. The percentage of organisations that plan to and already have implemented a Big Data project is 84%. Managers in organisations have rated the improvement of customer experience at 60%, the acquisition of more customers at 54%, and keeping up with competitors at 41% -the most critical factor in a Big Data project. The study has also demonstrated a tangible increase in revenue of a Big Data company by 88%. In comparison, their improved competitive positioning is increased by 92%, the ability to provide new products and services has increased by 94%, and companies have a 90% more targeted marketing campaign.

#DoingSomethingGreat means unlocking endless possibilities through the optimum use of big data.