Edge Analytics Driving IoT AdoptionEdge Analytics Driving IoT Adoption

Is your child's teddy bear spying on you? In yet another embarrassing example of connected "things" being improperly secured, exposing their owners to privacy breaches, more than 2 million voice recordings of children and their parents have been exposed online.

CloudPets, the makers of connected teddy bears, and a poorly-secured database are being blamed as the culprits.

While consumer connected devices are capturing the big headlines, there's plenty of adoption of connected things in business and industry as well.

MarketsandMarkets forecasts the Analytics of Things Market to grow from $4.85 billion in 2016 to $22.65 billion by 2021, a compound annual growth rate of 31.53%. The firm said that two driving forces for adoption are making IoT and its data more efficient and end-to-end automation. Business and industrial applications include energy management, predictive maintenance and assets management, inventory management, security and emergency management, sales and customer management, building automation, infrastructure management, and remote monitoring. There's a lot to unpack there for analytics pros.

A new IOT IT Infrastructure Survey from market research firm IDC also highlights the importance of solutions working with existing infrastructure as well as new architectures such as edge analytics.

"Given the strong uptake in IoT based technology solutions, enterprise IT buyers are looking for vendors who can add IoT capabilities to the current networking and edge IT infrastructure," said Sathya Atreyam, research manager, Mobile and IoT Infrastructure at IDC in a statement.

"Further, success of IoT initiatives will also depend on how IT buyers can effectively leverage newer frameworks of low power connectivity mechanisms, network virtualization, data analytics at the edge, and cloud-based platforms."

Data analytics, both at the central office and at the edge will play a key role in driving the adoption of IoT solutions.

IDC noted that the top vertical industries deploying IoT solutions were telecom service providers, high-tech, manufacturing, and construction industries.

Data analytics will play a key role in driving adoption of these IoT solutions, according to IDC. The firm pointed to particularly to edge analytics as growing in importance to organizations evaluating such technology.

If a "thing" in the field -- maybe a thermometer -- is generating thousands of data points that are the same, does it make sense to send every single data point to the central analytics location for processing? Or would it be better to just send the data point that is an anomaly? What if the thermometer is one of thousands of thermometers? Edge analytics enables the analytic computations to be performed at thermometer or sensor location. Then only the relevant data is sent back to the central location for further analysis and processing. This configuration can be particularly useful at remote locations that don't have unlimited network bandwidth.

Data analytics and governance professionals will have a great deal to contribute to the conversation about alerts, privacy, and other issues that come with the territory when dealing with important and sensitive data.