Defining data models for IoT workloads

According to the IDC, the sum of the world's data will grow from 33 zettabytes (ZB) in 2018 to 175 ZB by 2025. Additionally, the IDC estimates that there will be 41.6 billion connected IoT devices or things, generating 79.4 ZB of data in 2025 (https://www.datanami.com/2018/11/27/global-datasphere-to-hit-175-zettabytes-by-2025-idc-says/). Additionally, many other sources reiterate that data and information are the currency, the lifeblood, and even the new oil of the information industry.

Therefore, the data-driven economy is here to stay and the Internet of Things (IoT) will act as the enabler to ingest data from a huge number of devices (or endpoints), such as sensors and actuators, and generate aggregated insights for achieving business outcomes. Thus, as an IoT practitioner, you should be comfortable with the basic concepts of data modeling and how that enables data management on the edge.

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