The Internet of Things (IoT) is set to be one of the most disruptive innovations the world has ever seen. It will bring about a whole new paradigm of business possibilities. It’s estimated that over 30 billion smart devices will be connected to the IoT by 2020, and that could double as soon as 2024.
What does that mean for business owners? A few things. First, it means there’s going to be a whole lot of data recorded and stored from these devices. As a result, there will be potential data-driven insights on a scale that the world has never known before. Needless to say, legacy forms of data analytics aren’t going to cut it in the IoT world. This is why IoT needs self-service analytics.
1 Too Many Queries for Analysts to Handle
In a world where every device is connected to the Internet, there will be an unprecedented amount of data collection. However, this extreme influx of data will be overwhelming to some degree. This is why self-service analytics is going to be key to the IoT. There are going to be far too many queries for analysts to do all the work. Self-service analytics allows a broader group of users with permissions to contribute on a basic level. This will lower the workload of analysts and allow them to focus on more nuanced issues.
2 More Easily Scalable
As already stated, IoT growth is predicted to be extremely rapid over the next decade. Many businesses will struggle to keep up with this kind of expansion. Self-service analytics will allow organizations to scale their operations more easily. Executives will be wary of making decisions if there’s too much uncertainty due to lack of proper analysis. In a world that’s changing faster and faster, there’s also increased uncertainty about future specifics. Being able to scale analytics up or down based on present need will be essential for companies heavily invested in IoT.
3 Opens Up Insights from Whole Organizations
Granting analytics access to more employees frees up time for dedicated analysts to do in-depth work. However, there’s another benefit to getting more people involved with self-service analytics. This method allows actionable insights to come from anywhere, at any time. Consider the non-stop nature of supply chain data analytics. It’s highly inefficient to have someone from a different department troubleshooting one-time data queries.
By enabling workers on all levels to use self-service analytics, organizations will get insightful contributions from people who know their specific functions best. Further, engaging a whole organization with analytics as opposed to just a few individuals is a great way to spur engagement among employees.
4 Need Immediate Answers for Nonstop Workflow
The interconnectivity of IoT will make workflows move faster than they had in the past. While this is generally a positive thing, it can also bring some challenges depending on the industry. If one link in a supply chain is backed up, it can cause the whole operation to grind to a halt. The fast-paced nature of IoT will necessitate tools that can facilitate a nonstop workflow. This can be accomplished much more efficiently by granting analytics access to individuals working at each step in a supply chain. Otherwise, they might need to wait a long time before receiving actionable answers from the data team; and by that time, it might be too late.
IoT is going to completely change our world. It’s important that organizations prepare for this monumental shift by putting proper BI tools in place now. Self-service analytics is an essential part of this equation.