A few weeks ago, I had the pleasure of speaking at a \u201cMorning with Microsoft\u201d event in South Florida<\/a> with my colleague Chris Martinez<\/a>. Unfortunately, the event was during a regional cold snap, so I did not get to enjoy the usual balmy Florida weather. However, the engaging and invigorating dialogue around the positives and drawbacks regarding the Internet of Things<\/a> (IoT) more than made up for my disappointment in the weather.<\/p>\n IoT empowers organizations to gather, analyze, and employ information in ways previously unattainable. But this newfound capability is not without its challenges:<\/p>\n But we recognized these obstacles also present opportunities. Our presentation explored these topics, which set the stage for the mindful group discussion that followed.<\/strong><\/p>\n Tesla cars generate 25 Gb data PER HOUR! That\u2019s an insane amount of data that needs to be streamed, processed, and stored. Thankfully, public cloud providers, such as Amazon Web Services (AWS) and Microsoft Azure, feature multiple options for scaling IoT depending on your business goals.<\/p>\n Implementation options range from fully managed IoT SaaS models that require no cloud solution development expertise to IoT PaaS pre-configured solutions that give a little more flexibility to fully customizable IoT services for sophisticated implementations.<\/p>\n Additionally, we delved into the burgeoning field of Edge Computing. In traditional IoT scenarios, devices are \u201cdumb\u201d \u2013 assigned only to collect data and send it back to the cloud for processing. With Edge Computing, IoT devices are more intelligent, doing some of the processing themselves.<\/strong> This is especially helpful in situations with unreliable internet connectivity or in situations that require time-sensitive decisions.<\/p>\n We had a lively discussion around security and privacy. In general, attendees appreciated the advantages that IoT devices give including, health monitoring, business process improvement, home automation, and more.<\/p>\n But there was trepidation about how people and organizations can use the data unintentionally, or even worse, maliciously, to invade personal privacy.<\/strong> Examples included using personal health information from IoT wearables to deny health insurance coverage or personal assistants, such as Alexa, to monitor private conversations.<\/p>\n The consensus was that we need to keep IoT systems secure enough to keep out the bad guys (hackers), but also flexible enough to give good guys (users) power over their personal data\u2019s use.<\/p>\n IoT generates tremendous volume and velocity of information, which can cause a phenomenon I like to call \u201cDeath-by-Data.\u201d<\/strong> The data collects quicker than the user can process it, causing them to drown in their own information.<\/p>\n Often, the knee jerk reaction to this onslaught of information is to grab some visualization tools and jump right into slice-and-dice mode, creating all sorts of pie charts and bar graphs with their IoT data. However, at our presentation, we discussed a different approach that puts people first, followed by process, and finally, technology.<\/p>\n\n
The Discussion Explored These Topics<\/h2>\n
Architecting for Scale<\/h3>\n
Empowered Customers<\/h3>\n
Intelligent Data<\/h3>\n
This Process Included Asking These Questions<\/h2>\n