As companies continue to adapt to changes in big data analytics and the Internet of Things (IoT), there are certain trends which will shape 2017 that companies looking to maximize their ROI and productivity need to monitor.
The IoT and big data analysis have a broad impact on businesses, affecting areas such as risk assessment, risk management, and business strategy. According to a Business Insider report, proper IoT implementation and usage could boost business profit by lowering operational cost, increasing productivity, and enabling market expansion and new product development. However, businesses face well-documented challenges, such as security, that currently hampers the proper implementation and utilization of the IoT and big data analytics.
Some of these challenges and opportunities will be better explored in 2017. Here are some improvements expected in 2017:
Enhanced IoT Security
The security risk is one of the key challenges that has hampered the wide adoption of the IoT despite its potential. The risk to the interconnected devices, the platform, the communication, and the operating system is still a serious threat for many businesses. Enhanced securities that can shield IoT devices from physical tampering and information attacks, encrypt communications, and prevent battery-draining denial of sleep attacks will be available is 2017.
The challenge is that some of these interconnected “things have only a simple operating system that cannot support the robust defense software needed to keep out sophisticated hackers.
Data Analytics
Interconnected devices are projected to hit 34 billion in 2020. More businesses will start analyzing and exploiting the benefits of more interconnected devices to achieve various business objectives in 2017. For instance, big data is invaluable to marketers and the IoT will offer more insight into customers minds. Businesses will not only be able to better target and personalize their marketing messages, they will also be able to create more useful products for their customers.
Low Power, Short Range Networks or Low Power, Wide-Area Network?
Gartner projects that low power short range network will dominate the IoT space in 2017 through 2025, but will most likely co-exist with low power, wide-area network, and with no clear-cut winner between the two wireless network options.
Businesses and organizations will seek to balance several conflicting factors when selecting the right wireless network such as good battery life (up to 10 years), density, bandwidth, range, operational cost, and endpoint cost. The conflicting nature of it means most businesses may have to settle for a hybrid solution.
Recruiting Challenges
Many graduates want to work for tech companies that operate majorly around the internet such as Apple and Google, but there is a huge difference between the regular internet and the IoT. Companies in the IoT sector, such as those looking to create smart industries and cities, will still face challenges recruiting a skilled and effective workforce that will enable them to achieve their IoT-related goals.
For example, about 45% of companies currently face challenges recruiting workers that can secure the IoT according to a TEKsystems survey. So 2017 will be a year companies will invest in developing the required talent internally, while trying to recruit external talents that can provide the specialized skills needed to produce connected products.
Deep Learning
Deep learning has produced more hype than result in 2016. However, 2017 may just be the year some of its enormous business potentials are actualized. Deep learning is a machine learning technique modeled on the neural working of the brain that will enable computers and machine to recognize items of interest from a large set of data without the need of a specific code or programming to that effect.
Deep learning will make it easier to extract actionable information or data from big data with little or minimal supervision. For example, deep learning could play a huge role in image recognition.
Deep learning is already helping to meet the demand of intelligent video analytics. Intelligent video analytics makes it possible to analyze and process huge streams of footage, enabling businesses and organizations to detect abnormalities, track moving objects, and generate alarms that enable organizations to take appropriate actions.
Many of the processes mentioned above will not be perfected in 2017, but significant progress will be made. It’s expected that some traditional businesses will be disrupted as IoT matures, and 2017 may help make things clearer and help such companies that may be affected or disrupted adjust accordingly.
