Things are getting smarter. Yes, you read that correctly—we’re referring to ‘things’. In the blink of an eye, we began witnessing new initiatives that leave us in awe, from home robots to supermarkets or smart cities, all thanks to technology and something often overlooked: the tremendous human effort behind it.
At Keepler, we’re at the forefront of navigating the complexities of the Internet of Things (IoT), a phenomenon that has seamlessly woven itself into the fabric of our daily existence. What was once the preserve of the technologically elite has now become an integral part of our domestic landscape.
Now, using a Smart Homes company as an example, let’s materialize what this means. In Spain, with almost 49 million people, imagine this Smart Homes company holds a 5% market share—that’s about 2.45 million homes with sensors and connected devices generating information 24/7. Can you imagine the amount of data this can produce? If, on average, each smart home has 10 devices or sensors connected, each producing around 1 megabyte per day, we’re talking about approximately 23.93 million gigabytes of data to manage and store every 24 hours. Now, calculate how much this means per month, per year… an endless stream of data constantly providing information. It’s clear that when we talk about IoT, we find three characteristics we cannot ignore: its complexity, its connectivity, and its unprecedented scalability.
IoT Data Governance, main components (Keepler, 2024).
The massive volumes of data produced by this plethora of devices underscore the vast complexity inherent in IoT, compelling us to fortify our ecosystems with advanced management systems. These systems must evolve not just from their technical layers but also from a business perspective—or as we prefer to say, “The Human Layer”. For a company to unlock the true value of this data, it must understand “how” individuals interact with this technology and must establish a set of rules, procedures, and responsibilities for collecting and leveraging data effectively. In other words… (well, you might guess what’s coming next): this information needs to be governed.
Data Quality: A Must-Have
A Data governance and management strategy allows the Smart Homes company to ensure the quality, security, and privacy of its IoT devices. As we’ve seen earlier in the article on data privacy, a large amount of data comes with great responsibility.
The ecosystem in which IoT is deployed has another important characteristic: the speed at which its information is required. Now, imagine applying this concept on a larger scale, as in the case of a Smart Airport.
A Smart Airport relies on a network of sensors and connected devices with specific objectives in different areas to monitor, manage, and coordinate its operations centrally. Today, thanks to IoT application, it’s possible to improve staff performance, optimize passenger flow and satisfaction, and increase airport security. A clear example of the benefits of proper governance is the use of IoT to collect valuable, real-time information about the state of planes, facilitating more accurate and efficient maintenance planning, increasing flight safety, and optimizing investment.
The efficient implementation of a data office can ensure this information remains reliable by identifying roles and functions that act as guardians of the main data quality dimensions. These dimensions are measurable attributes that would help the Smart Airport define quality requirements. By controlling these dimensions, the airport ensures its information is reliable and reflects reality, especially in terms of consistency and accuracy.
The Data Quality Wave by Keepler in IoT
Natural progression of data quality (Keepler, 2024).
To apply data quality, one must consider both syntactic and semantic rules. This is where the technical and non-technical must meet and align. Normally, when referring to quality rules, they are automatically associated with technical teams, overlooking the business people who often represent a significant percentage of the demand for this information. These standardized procedures by technical teams, serving for the evaluation and improvement of data quality, must be implemented using business rule-based techniques. Non-technical users must actively participate in defining and modifying these rules based on the business objectives of the organization.
This is why at Keepler, we consider quality rules a business conceptualization and have developed a working framework we call the Data Quality Wave. Through this method, developed in six phases, we ensure covering all key points on the path to optimal quality. The aspiration of a quality program is to achieve syntactic accuracy, ensuring the construction of the field is correct, and semantic accuracy, validating its content. In other words, our framework guarantees that data is stored according to its nature and the reality of the business.
Understanding the Value of IoT Data
For businesses, grasping the value of data generated by the IoT is crucial. This valuation can be conducted through a Data Value initiative, thereby maximizing the return on investment from technological ventures. At Keepler, we recognize the significance of quantifying this value and have developed a methodology known as the Data Value Framework. This framework enables us not only to understand but also to calculate the economic value that IoT data brings to an organization. By managing and analyzing collected data, we identify how it is used and the value it generates, allowing companies to gain a competitive edge. For instance, within the Smart Airport context, data gathered through IoT can lead to more accurate planning that reduces costs, enhances customer satisfaction promoting loyalty, and improves security, ensuring compliance. Thus, data value becomes a cornerstone for strategic decision-making and process optimization, enabling the organization to pinpoint the core activities that yield a higher economic return.
Data Management Associate at Keepler. "I'm an innovation enthusiast that helps companies govern their data and digital transformation. I love learning by doing and not afraid of new challenges. For me, the sky is not the limit."
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