Ronald van Loon: “Data from IoT exists within the realm of Big Data and the large quantities of data that it represents”
01 Mar 2017 IoT General
Ronald van Loon is an expert in Big Data, Data Management and IoT. His work helps hundreds of companies driving and generating value from the data they manage around the world. He is director of Adversitement, a company that provides consumer data analysis; and he is one of the largest influencers in the world at Big Data. For all of this, we have asked him to give us his insight into the important role that Big Data plays in IoT, as well as the main challenges to be faced and the future that holds companies in relation with the Internet of Things.
1. Big Data is an expression that can be ambiguous. Also, it is usually misunderstood. In your opinion, what would be the most accurate definition of it?
Big Data is all of the data that is being generated by social media, digital processes, as well as systems and sensors, and it’s being produced in increasing volumes, variety, and velocity. It’s capable of providing meaningful value and insight for businesses who possess the right skills and capabilities.
2. In general terms, what is the role of Big Data in IoT?
Data is at the forefront of any IoT application, and there is a distinct relationship between the two. Simply stated, IoT includes data, devices, and connectivity, whereas Big Data is solely about data. Sensor data is a new high volume, high velocity and variety type of IoT data that is essentially the output of a device that’s responding to input from a physical environment.
3. Could there be an “Internet of Things” without massive amounts of data?
No, because IoT is about the data that’s produced from devices, or “things,” and the collection and sending of data between devices. Data from IoT exists within the realm of Big Data and the large quantities of data that it represents.
4. Within Big Data, what are the main sources of information coming from devices connected to IoT?
The main sources include transport, such as a car, train, airplane, and also machines, energy, buildings, healthcare devices, cities, wearables and retail RFID.
5. If we could define some, what would be the most famous and useful techniques and processes within this sector?
Machine learning and all its different algorithms, which has enabled businesses to benefit from improved performance in diverse areas including “digital twins”, cognitive commerce, self-driving cars, predictive maintenance, smart buildings and many other IoT applications.
6. Let’s talk about the future. The development associated with Big Data, where is it heading?
Big Data will only become more relevant in the future, with more data, more sources (including devices), and more velocity. Also, more mature analytics, from predictive to prescriptive and cognitive.
These developments will lead to a substantial improvement in the customer experience, allowing businesses to provide more personalized and relevant experiences. In the last two years alone, 90% of the world’s data was generated. Given that IoT is an extension from the customer journey that generates a substantial amount of data, growing from 10 billion devices to 34 billion devices in 2020, the volume of data ready to be processed by Big Data solutions will only increase.
7. Another important question: what are the major challenges associated with this Big Data? Like problems, there are also solutions. What techniques are most promising to solve the new challenges of Big Data?
Major Big Data challenges include how to manage data governance from all sources and people, handling data correctly and ensuring it is only assessable by the essential parties. Data quality and consistent definitions is another challenge, because businesses need accurate, high quality information for better decision making capabilities.
A Data Management Infrastructure of Tomorrow provides the solution; it is fundamental for predictive, prescriptive, and cognitive analytics, all necessities for businesses who want to remain competitive and benefit from instantaneous resolutions.
8. What is the attitude of companies when facing Big Data? Are they aware of its real value?
Companies want to become data driven but face organizational challenges, and need the right expertise, capabilities, and resources to derive value from Big Data. They often lack the knowledge to build and use the right technology stack. In practice, 85% of companies are only just starting to explore by trial and error, and attempting to obtain data value.
Many organizations have small, advanced analytics teams that start deriving first value out of Big Data. And most companies are working on compliant digital analytics and begin experimenting with predictive analytics.
9. How will be the Data Management of the future? Do you need a fundamental change in data analysis, and its infrastructure, to support it?
An increasing number of companies are adopting a holistic approach to data management, with collaboration and coordination to share data throughout an organization. Businesses need to take a proactive approach, move away from the silo mentality, and create agile, multidisciplinary teams that can effectively share information, optimize productivity, integrate data, and better serve customers.
10. What is the role of the user/customer within Big Data? Is he simply “a generator” of information or much more?
In the context of Big Data, the customer is the driver for using data driven solutions to improve and refine the customer experience.
11. Talking about IoT, what are the most promising solutions to these two concepts: Internet of Things and Big Data?
IoT and Big Data are facilitating a network of smart cities, digital twins, cognitive commerce, self-driving cars, cognitive electronics, smart buildings, predictive maintenance, and transforming the healthcare industry.
12. What are the most interesting projects within IoT that involve the use of Big Data that are currently under development?
Recent IoT events feature real life examples of large scale projects with maximum potential. To mention a few examples, Visa is turning devices into point-of-sale, Ricoh is introducing a cognitive, interactive whiteboard to improve business meetings, Airbus makes Digital Twin come to life, Visa embraces cognitive commerce, SNCF and Trenitalia Railway run smoothly with predictive maintenance, Bosch makes industrial IoT a reality and so on.