Blog Series: IT Perspectives by Jaqui Lynch

In my last blog, “What To Do With All That Data,” I talked about Big Data and how we define it. One of the key contributors to the need to work with Big Data is the internet of things (IOT). The IOT is where data comes at us from multiple sources and we need to be able to take those sources and process them in some kind of meaningful way. We define the IOT as the network of physical objects that are embedded with electronics, software, sensors and network connectivity that enables these objects to collect and exchange data. These physical objects can range from devices, vehicles, buildings, rockets, watches, clothing and many other items. These are the days of smart fridges that can place orders for you and of cars that need no drivers. The IOT revolves around machine to machine computing, taking advantage of cloud computing and huge networks of data gathering sensors and devices. People talk about smart houses and smart lighting and so on – what they are really talking about are devices with embedded sensors that can be controlled remotely and/or that can make autonomous decisions.

It’s essential

According to Cybertrend’s March 2016 magazine, “new research from Gartner suggests that business intelligence and analytics solutions are now becoming an essential component of successful business strategies.” People are looking for solutions that are led by the business and that incorporate self-service wherever possible. The IOT provides the data that, when properly integrated into an analytics solutions, allows them to make better business decisions rapidly. Gartner actually expects the BI and analytics market to grow 5.2% over last year, reaching $16.9 billion in 2016.

It’s complex

The challenge with the IOT is its impact on three of the four V’s of Big Data – volume, variety and velocity. The sheer number of objects creating data leads to data sets that can be petabytes or exabytes in size. Add to that the speed at which that data accumulates and there is a real need for significant network and computing bandwidth in order to process that data in a timely manner. Finally, the data coming in varies significantly depending on the devices that create it.

In industry machines are being updated to provide data that, when combined with operational and environmental data, allows companies to turn that data into operation insight to improve daily operations. The data can be used to predict the declining health of machines and to predict failures. Additionally, companies are adding “phone home” features to products so they can provide ongoing data as to how they are being used and on the health of the products.

It’s personal

And then there are the consumer products. Like many people I have a smart watch. Mine is a Garmin Vivoactive. It keeps track of my exercise and uploads it to the Garmin and Weight Watchers sites. Many people have similar watches or devices that upload data wirelessly. Most pacemakers that are installed today have wireless capabilities that allow them to monitor and report on how the pacemaker and patient are doing. Many cars today have wireless capabilities that allow them to report problems and on how the car is behaving. And most security systems now connect wirelessly instead of via a phone dedicated line.

It’s challenging

This mass connectivity gives rise to several issues. The first is the need for significant wireless and network bandwidth. There is also the increased dependency on the reliability of those connections. But the bigger issues are around security and privacy. In many cases people are not aware that their devices are reporting data. This is the case with many of those who wear pacemakers but also with security systems and other devices. If someone hacks your Xbox or PS/4 it hurts but is not a huge deal. But if someone hacks your pacemaker or car and takes it over that becomes a huge deal very quickly.

We now live in a world where huge amounts of data are being recorded and stored about us and where that data is being used to make life altering decisions. Software bugs could actually kill you as could a determined hacker who manages to break in. Forrester has actually predicted tha 2016 will be the year we see ransomware for a medical device. That is why it is important that these devices have built in features like encryption, authentication and remote update capabilities. It is critical that life sustaining or altering devices have protection that makes them difficult to take over.

I keep hearing car manufacturers talk about how their cars have computers that will put the brakes on automatically if they sense you are going to have an accident or are too close to the car in front of you. While that may be great in theory, it is not so great if someone hacks into the car system and decides to take over the car for you. Multiple hackers have shown already that you can hack into these cars. And many of them have multiple computers in them so there are multiple targets to go after.

It’s insightful

Apart from security the other major concern is around privacy. Using BI and analytics software companies are able to amass huge amounts of data about people and how they behave. This allows them to make better business decisions and to target sales campaigns in a more personal manner. The negative side of this is that all that data is stored together and makes it easy for someone to steal your identity if they get access to it. The areas of security and privacy have been overlooked as the IOT has taken off and it is only now that companies are taking a step back and realizing that they need to spend time seriously reviewing not just the data but also how that data is accessed and how it will be protected.


There are incredible advantages to the embedded smart computing involved with the IOT. Imagine bridges using smart concrete that monitors the bridges safety and notifies the computers in cars if there is ice or if the bridge is becoming unsafe. Smart stoplights could monitor traffic flow and make changes to their normal behavior based on that. Smart watches could monitor your health and automatically make appointments for you if they determine that you are getting unwell. There are significant savings involved with lights turning on and off as you enter and leave rooms, or your car determining the best routes to take. And all this new information leads to new products and new services which leads to potential new jobs.

Additionally, there is the need for more storage and compute capacity to store and analyze the huge volumes of data produced. And it is not just about the savings and the ability to make better decisions, it is also about generating a whole range of new product offerings that can be more personalized. However, all of this needs to be balanced with the need to protect consumer privacy and to provide security on both the data and the sensors providing the data. This is where the real challenges lie.

Schedule a consultation today to learn how Flagship can help you design and implement an effective big data solution.

If you liked this blog, you also might like:  What To Do With All That Data

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