Mar 06, 2017The Internet of Things universally connects people, mobile devices and machines via networks. The implications of this sea change for business, government and all of society is only just beginning to show. IDC predicts that the IoT's installed base will be roughly 212 billion machines and devices worldwide by the end of 2020. This includes 30.1 billion installed connected (autonomous) things.
Organizations were the generators of the majority of their data before the IoT came along. This included files, presentations, spreadsheets and databases. They sent this self-generated data to a centralized repository, then stored it until they could analyze it. During the data warehouse era, organizations ran their operations and made decisions based only on this warehoused data.
Gaining intelligence from this centralized data could take days, weeks or even months. It could take even longer to make decisions based on these findings. In the age of the IoT, that's not fast enough, and it leaves out too many additional sources of valuable information.
There has been an explosion of unstructured data—big data—during the last half decade, It's coming from Google, Amazon, Facebook and Twitter. It also comes from mobile devices like smartphones or tablets, and from machines such as smart oil wells. The IoT generates massive amounts of big data every instant about how people are living, working and purchasing, and how machines and networks are operating. These days, organizations need critical unstructured data in addition to data they create. Based on this data, they can ask questions they weren't even capable of posing before, let alone answering.
Taking Data to the Edge
A completely new method of detecting patterns is now possible because of the IoT. It is called
edge or "fog" computing. Fog computing takes place right where people are using mobile devices, and right where sensors are tracking and reporting performance and condition within industrial systems.
An example of an edge activity captured in the big-data torrent would be a sensor in an oil rig that checks for damage to critical valves. The sensor's signal can be tracked and analyzed using fog computing.
The caveat with big data is that it has a short half-life. Even if it takes only hours to get to a data center before it is analyzed, big-data risks becoming obsolete. If the rig's sensor reports a sudden change in pressure, the valve might fail before the rig operator knows there's a problem.
This is why it's necessary to analyze big data at the network edge—right where people, devices and machines are generating it, and right when a decision based on the intelligence from that data can make a difference. Storing data in a warehouse and waiting on decisions doesn't cut it anymore.
The Power of Connection
People, process, data and things are now hyper-connected due to the IoT. This is what makes big data so significant. Hyper-connection alters the role of information and promises tremendous opportunity.
Big data makes it possible to improve the quality of each decision an organization makes. How much value it obtains from the IoT depends on how well it secures, aggregates, automates and draws insights from its data and its big data—and on how quickly it does so. Over time, the results can pay off in a big way. If the rig operator discovers a valve flaw in time to replace it during routine maintenance, this can avert the huge cost of an unexpected shutdown.
Facing the Challenges
Technology challenges arise when organizations begin their digital transformation. These include stronger engines to accelerate applications and power data-intensive analytics. An operating environment that is common to the data center and the edge sources of new computing must bridge traditional and emerging applications and manage varying workloads better.
Forty percent of companies surveyed in a Cisco study identified big data as the element that most needed improvement within their organization. Almost 40 percent said that within three years, smart devices at the network edge will process most data. They also identified analytics tools for big data as the most important enablers of connected device networking.
They highlighted four areas for improvement that would make effective use of the IoT:
Process: Updating business and operational processes.
People: Enabling workers to exploit the IoT through training and easily used systems.
Things: Connecting the right machines, devices and equipment to capture truly useful data.
Data: Capturing, storing and analyzing information from connected machines and devices.
Organizations are just starting to get their arms around the IoT, a sort of undiscovered country that offers glimpses here and there of incredible opportunity. However, there are dragons lurking about as well, in the form of speed and technology challenges. As organizations overcome these challenges, they stand to reap rich rewards.
Neeraj Chadha is the product manager for Learning@Cisco at Cisco Services.