Posted on October 24, 2018 by Jessica Ciesla
Just a few years ago there were roughly 15 billion devices connected to the IoT, or "Internet of Things". By 2020, that number is expected to grow to 30.7 billion - representing about $1.29 trillion across all markets. Countless products - from industrial sensors, workspace management applications, to wearable devices - are all connected to the Internet, and to each other. This is allowing them to create and share valuable data every second of the day.
For business leaders, this is cause for celebration - to an extent. While it's true that IoT as a concept brings powerful benefits in terms of productivity, efficiency and cost savings, it also brings with it its fair share of challenges. These challenges often lead to projects stalling out before they've even had a chance to begin.
In this blog post, we’ll go into detail about the top three challenges you are most likely to face when beginning an IoT implementation - and how to address them in the most effective ways.
The Art of Data Integration
When shifting towards IoT, the most immediate challenge that businesses face is the concept of data silos. Simply put, data isn't adding anything of value to an organization if it exists in a vacuum. If data created by the marketing department is cut off from the sales department, how is it benefiting the most important person of all: the customer?
When addressing this challenge, organizations typically have two options available. They can choose to buy or create a new end-to-end solution from the ground up, or they can better incorporate and integrate IoT functionality into their existing infrastructure. The former solution is costly, to say the least - which is why many organizations tend to prefer the latter. Regardless of which path you choose, it's clear that integrating data from existing systems - whether you're talking about business applications, legacy systems, machine data, or something else entirely - is absolutely a step worth taking.
The Value of Data Quality, Filtering and Enrichment
To say that the consequences of poor data quality can be disastrous is an understatement. Incorrect or delayed decisions, spending money that you don't need to and sowing the seeds of distrust between departments - these are all things you face when you treat all data equally.
Big data - and, as a result, the Internet of Things - only heightens this challenge. There is, however, something that you can do about it. By making an effort to have the right data integrator at your side, you can not only cleanse data generated by IoT to make sure it's actually valuable, but you can also enrich and manage that data at the same time. Data from a relational database, for example, is typically unstructured, while social media data is often unable to be understood in raw form by even the savviest marketing manager.
A data quality tool, on the other hand, can help generate real-time alerts on mission-critical data discrepancies and other problems now. This allows you to fix small issues today, before they have a chance to become much bigger (and more expensive) ones tomorrow.
The Power of Analytics
Once you've made an effort to integrate, filter and enrich your data, the next important challenge is figuring out how to present it. You have to find the right way and the right people to target, while also finding the correct time. After all, IoT data is ultimately meaningless if you can't unlock the true narrative and insight hidden beneath all those 1s and 0s.
For this, many businesses are turning towards powerful analytical tools. When you have the right analytics solution at the heart of your organization, it makes things simpler. From decision makers being able to access data they need at the exact moment they want it, to using it to visualize the data and elevate it above and beyond its original form.
But again, analytics are about more than just "making sense of data." It's about cutting through the massive amounts of noise being generated by IoT, allowing insight and action to rise to the surface. It's about processing data and making it available to all levels of an organization in real-time. It's also about an almost unprecedented level of visibility into your operation, being able to see what's going on with a granular focus, so that you can make better, more informed decisions faster than ever.
Yes, the Internet of Things brings its fair share of challenges. But the benefits far outweigh the potential downsides, particularly once you begin to realize with the right solution those "downsides" are far smaller an issue than what you gain from integrating with IoT.
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