The Internet of Things (IoT) has captured the imagination of a lot of us. Yet, in many ways, the technology is still in its infancy. Not least because although many businesses want to use IoT tech… they’re just not sure exactly how best to do it. Integrating IoT data management can be a challenge. It requires a top-notch approach, but many organisations are stilted by legacy systems or poor data infrastructure.

All successful data projects are rooted in effective data management and governance. IoT is no different, in fact, it requires more than just your standard practices. When it comes to IoT data management, ensure the data you collect is of good quality, trusted, secure, and in the right format. Just like any other data you use.

Defining IoT

In its broadest sense, IoT encompasses any device attached to the Internet. Usually, it involves a previously offline (or dumb?) device that is connected to the Internet or other devices via a chip or sensor. Now, we have everything from smart kettles, to IoT-enabled construction sites. By 2020, It’s expected that over half of all new business processes will involve IoT. The wealth of data that businesses can potentially collect via IoT makes it a very attractive asset for many. Every business, from retailers with beacons in-store, to manufacturers with sensors embedded throughout the supply chain, can benefit from using IoT.

Getting on top of IoT data management, therefore, is a good way for a business to top its industry in the next decade or so. As such, you need to lay the right foundations. The success of your IoT project lies in the way you manage its data.

The data management of things

Collection and storage of IoT data have a lot in common with other data sources. In other words, the processes you follow for other data projects should be the same for IoT. There is still an onus on using good data governance practices to ensure your data can be trusted. Data analysis cannot be reliable if the data put into it isn’t up to scratch.

Integration of IoT

To get the most value from your IoT data, integrate it with all your other data sources. No data should be an island, and IoT is no exception. Of course, this poses challenges in how to integrate your IoT with existing data and legacy systems. You’ll need to look at your entire existing architecture, to determine where IoT fits in.


A critical first step to using IoT data effectively is to have a system that continuously collects data in real-time. IoT data is real-time, which raises the stakes for data management. By the time this type of data reaches a data warehouse, it’s already outdated. You simply cannot gain value from it in this way. Therefore, a streaming-first architecture (where you get insights from data as soon as it is created) is needed. Change data capture that transforms your database data into data streams, will enable your other data to be integrated with IoT data.

IoT security

The security of IoT data is a huge challenge for organisations. Indeed, over half of security leaders surveyed have stated that they are extremely anxious about IoT security. The more devices you have connected and collecting data, the more difficult it becomes to secure and monitor them all. Plus, some IoT data (like biometric data collected from wearables) is highly sensitive in nature and will require more robust security.

The same survey found that 82% of security leaders weren’t sure who had ownership over IoT data. Given that ownership of data and data processes is a fundamental part of good data governance (as outlined in an earlier blog), this is a very worrying situation. Without someone who owns the data, the rest of your data governance will not work well.

Real-time data = real-time problems

A big characteristic of IoT is the ability to get real-time responses. At the click of a button, someone can make an order. With a word, someone can check the weather. IoT users expect to request and access information immediately.

Take a proactive approach to identify any issues that might arise with the technology. Unlike with other data processes, you cannot have an issue present for hours. Ensure there is a way to check for problems throughout the day; a dashboard (that is always on display) to monitor for issues, and to measure the health of your data, is a good idea.

Have a recovery plan in place. With real-time data, things might go wrong sometimes. Swift response requires a clean line of command and reporting processes. If communication with the public or other stakeholders is needed, have an appointed spokesperson – and ensure everyone knows what (if anything) to say.

Walk before you run with IoT

It’s worth doing some other data analysis before jumping headfirst into IoT. IoT is complex and requires some specialist knowledge and skills. In order to gain buy-in for your ambitious IoT plans, first prove the worth of using data at your organisation. Get some quick wins under your belt and it’ll be a lot easier to demonstrate the value of IoT to your board.

Do you need IoT?

Using IoT might seem like something innovative and new to explore, however, there needs to be a good reason to use it. Consider your use-cases and ultimate data goals. What do you want to achieve and does IoT data help with this?

A retailer, for example, might want to help bridge the gap between its online shop and brick-and-mortar stores. Beacon technology can be used to track customers through stores and to understand which aisles people stop in. Tailored promotions can be sent to those customers, based on if they spent more time looking at, say, dresses or at shoes. Beacons can push those offers direct to their phones in-store, or alternatively through digital marketing campaigns later on. Smart mirrors in changing rooms can suggest items to customers in-store or help people browse the webshop.

Of course, all of this needs to be scalable. The real-time aspect of IoT needs to apply whether you have one store or thousands across the globe. Time-out issues because of poor data management will annoy customers quicker than you can say “Mirror, mirror, on the wall…”

Build strong foundations first, IoT will follow

IoT might be the future, but to use it effectively – consider the past. Go back to basics and ensure your underlying architecture is the best that it can be. Build strong data foundations to stop your IoT ambitions from crashing down. Security of your IoT data must be a priority.

Consider whether you need to use IoT in the first place, and make sure you have the right skills in-house. Gaining buy-in is also crucial, so it’s worth doing other data projects before experimenting with IoT. Best practice will get you through with IoT.

For more insights into your data management and governance, make sure to download our Data Management white paper.


Written by Jason Foster


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