As connectivity around the world continues to grow, one consequence of this is there will be an enormous increase in the number of devices able to gather data and send it back to businesses. These are not only limited to traditional connectivity gadgets such as smartphones, but a wide variety of sensors and other items that will be able to collect information on almost any parameter, whether in homes, factories, workplaces or vehicles.
This is called the Internet of Things (IoT), and it’s set to be big business in the coming years. Gartner estimates there will be 4.9 billion connected devices in use around the world this year – an increase of 30 per cent on 2014. However, this pales in comparison to the heights the technology is expected to reach in the coming years. By 2020, the market research firm predicts there will be 25 billion IoT gadgets in use, while International Data Corporation estimates the market will be worth $1.7 trillion by that year.
The next big thing for IT
But what is IoT, and what will it mean for the data analytics sector? In truth, the term covers a wide variety of devices, but it essentially boils down to equipping items with electronic sensors and connectivity that allows them to communicate with each other or central services.
This could be GPS devices on cars that inform insurance companies about an owner’s driving patterns, manufacturing applications that can alert users when maintenance is required for machines, or even domestic uses such as climate control apps or refrigerators that can automatically order groceries when supplies run low.
This means that regardless of the industry they are in, no company can afford to ignore the potential of the technology. Companies that do not have access to IoT data will lack crucial insights into their customers, preventing them from making appropriate decisions to increase their profitability, boost service levels and develop longer engagements with customers.
Challenges for analytics
But this will lead to a range of challenges for companies looking to incorporate IoT insight into their operations – particularly when it comes to gathering, storing and analysing the data that these devices can generate.
For starters, businesses need to have plans in place for how they will cope with the huge volume of data they can expect to receive, as well as dealing with a wide variety of mostly unstructured data. This is where tools such as Hadoop, which are capable of cost-effectively storing, processing and analysing this type of information, can prove highly useful.
Businesses also need to bear in mind the privacy implications of IoT, particularly when dealing with consumer oriented applications. With so many devices expected to gather data on almost every aspect of people’s lives, from what products they buy to what their movements are, there will naturally be concerns about how this information is used – both directly and indirectly. Therefore, companies must work hard to reassure their customers they have strong security and be transparent about their information processing activities – including any sharing of data with third parties.
A wide range of applications
When it comes to applying IoT solutions to a business’ operations, the possibilities are almost endless – and are already being used in a lot more places than many people realise. For example, gadgets such as the Apple Watch and Fitbit activity tracker feature sensors that can monitor the health and fitness of their wearer, providing information and advice. This is just one instance where IoT technology is being integrated into consumer products, but it’s far from the only option for IoT.
The real benefits of this technology are likely to come from more large-scale commercial and industrial applications. For instance, adding sensors to utilities infrastructure to create smart energy grids can enable suppliers to dynamically adjust their output in response to demand, or identify areas of the network where maintenance is needed.
Similarly, manufacturers can use IoT sensors to boost efficiency, while operators of transport services can keep an eye on their entire fleet and be alerted to any problems before they become a major issue. But whatever the use case, in order to be successful, an IoT deployment will have to be backed up by an advanced analytics solution that is able to take data from these disparate sources and translate it into actions – with or without the intervention of a human operator.