The Internet of Things (IoT) will open your data flood gates and your IoT platform needs to scale to the challenge.
In his book "The Age of Spiritual Machines" Ray Kurzweil narrates a story about the inventor of chess and the emperor of China. The emperor was so pleased with the game that he offered the inventor a reward of anything that he wanted. The inventor replied that the emperor could give him a grain of rice for the first square of the chessboard, multiply that by two and give him two grains of rice for the second square and multiply this again by two and give him 4 grains of rice for the third square on so on till all the squares of the chessboard were covered. The emperor smiled and granted his request.
As the officials began to place rice grains on the chessboard, things were fairly quiet in the beginning. By square 32, the emperor had given away 4 billion grains of rice, one large field's worth and the emperor started taking notice. Things start escalating rapidly in the second half of the chessboard. Someone in the royal finance department figured out that by the time the last square would be filled, the emperor would have to give away 18 million trillion grains of rice, more than what was grown in the entire planet. That’s the power of exponential growth.
When you connect to your devices on the field and start talking with them, soon you are going to run in to an exponential growth problem. As you implement your initial set of use cases and start collecting more data, connecting more products and rolling out across more geos the data starts growing exponentially and your value realization is dependent on your platform's ability to manage and make sense of this data. Your IoT platform should be scalable and flexible to manage this challenge.
It is not the enterprise scale; it is the internet scale.
Enterprise scale, in this context doesn’t cut it. Here are some of the challenges that your IoT platform needs to handle:
- Volume, velocity and variety - The platform should be able to handle the well quoted 3Vs of Big Data - volume, velocity and variety. The volume will quickly scale from Tera bytes to Peta and Exa bytes. The velocity will shoot up when data is processed in batch mode or periodically to near real time or in real time. There is a variety of data types and sources– structured vs unstructured, tables, databases, images, mobile, machine to machine which needs to be managed.
- Proliferating product lines and large installed bases - A large industrial company could have tens to hundreds of product lines and an installed base running to millions of units. The platform should be able to support these different kinds of machines and the parameters being tracked, and flexible enough to keep adding new products and new parameters.
- Multiple stakeholders and role diversity - From an end user perspective, the platform should enable the right visualization and analytics for managing the different types of end users and the diversity of roles and decisions. The different kind of stakeholders could be R&D, product management, industry verticals with customer ownership, end customers and after sales services units. The use cases and the decisions to be enabled by IoT for each of these groups are different.
To handle these challenges, your platform needs to be internet scale and not just enterprise scale.
As we have seen things get hectic in the second half of the chessboard. Will your IoT platform be ready?
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