Big Data is another technology buzzword that can sometimes be difficult to pin down. Data, of course, has been around for a long time, long before computers invaded our homes, offices and pockets, so what exactly differentiates ordinary data from Big Data? Broadly speaking, Big Data refers to datasets that can no longer be processed through traditional methods of analysis. This means that setting a minimum boundary for what constitutes Big Data is extremely difficult, as this value would likely change with each technological development. What is clear, however, is that Big Data is growing rapidly. The rise of digital technologies, particularly smartphones, has meant that the amount of information that we freely share, knowingly or not, is enormous.
However, Big Data is not just about the amount of information being produced. Data now comes in many forms, ranging from website cookies to social media posts, which means that processing this information is not easy. The unstructured nature of data in the modern world has led to the rise of ever-more advanced analytics programs attempting to make sense of the data deluge. Generating insights from Big Data could be hugely lucrative for businesses, which is why the Big Data industry is predicted to be worth $ 41.5 billion by 2018. Big Data can enable firms to learn more about their customers and competitors, ultimately driving up revenues and facilitating business success.
Advantages for businesses
Some common Big Data advantages include:
- Insights – The goal of Big Data analytics is to generate insights that translate into tangible business benefits. These could be relating to real-time events or even future trends. Big Data insights are now being used across a wide range of industries including healthcare, transport, retail, marketing and many others.
- Customer feedback – There more ways than ever before for customers to interact with your business, but this can make it difficult to develop a coherent picture of how your product or service could be improved. With Big Data analytics, unstructured information can be analysed, such as social media posts, giving businesses a better understanding of your customers’ views.
- Risk mitigation – Big Data can help companies to make informed decisions when it comes to risk assessment. Financial institutions, in particular, can collate information from multiple sources to gain better visibility into customer behaviour, reducing the likelihood of fraud or financial mismanagement.
- Cutting costs – Although effective Big Data analysis does require some financial investment, it could save your business significant sums in the long run. Manufacturing firms, for example, are now using analytics to better assess the lifespan of their equipment, so that it is only replaced when necessary. By analysing vast quantities of sensor information, businesses can get a better idea of when a component is likely to fail and when it still has plenty of life left in it.
As with many new technological phenomena, Big Data has not been without its teething problems. Many of the challenges facing organisations centre around data collection, and specifically whether the public are made aware of when their data is being collected and what it is being used for. We now live in an age where so much information about our daily lives is widely available. Smartphones keep a constant record of our location, our social media profiles record our likes and dislikes and application permissions often ask for more data than is seemingly necessary. In a post-Snowden world, individuals are more aware than ever that their personal data is a valuable commodity. It is up to businesses, therefore, to use Big Data transparently and responsibly.
Businesses that are overzealous with their data collection risk alienating their customers. A number of studies have been conducted that evaluate when customers are willing for their data to be used and when they are not. For example, a recent survey carried out by CSC found that 73 per cent of shoppers were not comfortable at all, or not particularly comfortable, with in-store technology that tracked their behaviour. Shoppers were, however, more receptive to data collection when there was a clear and justifiable benefit to the customer. Businesses must convey the purpose of any Big Data collection programmes in advance if they are to avoid a customer backlash.
Data storage is another challenge that businesses must overcome. Big Data has meant that organisations are storing more consumer information than ever before, some of it of a highly sensitive nature. This increases the fallout of any data breaches, so companies must ensure that their security protocols are robust enough to safeguard valuable information. In addition, businesses should be careful not to share customer data with third parties without public consent. Businesses that sell on consumer data can experience reputational damage if that data is then used irresponsibly.
How to use Big Data effectively
Given the competitive nature of many industries, some businesses have fallen into the trap of thinking that more data automatically equals better insights. Of course, the vast quantities of information now available to companies could prove hugely valuable, but only if businesses use them effectively. Using up-to-date analytics software is one way of generating insights from Big Data, but businesses would also do well not to neglect the human talent at their disposal. Data scientists are hugely important for using Big Data effectively, as they can help businesses to identify the right questions to ask. Having vast stores of data is all well and good, but what do you want it to tell you? Are you trying to improve customer retention? Turn leads into sales? Or make prediction about future trends? Without a clear understanding of what you want to get out of your data, useful insights are unlikely to be forthcoming.
For businesses exploring the potential of Big Data there are many benefits to be had. However, misuse of data could also have harmful consequences. Transparency is vital if organisations are to successfully use Big Data to their advantage. Trust must be cultivated between businesses and customers so that Big Data becomes the vehicle for a mutually beneficial long-term partnership.