3 Foundational Practices for IoT Data Processing

IoT isn't just a capability you plug into an existing enterprise architecture. It requires validating existing capabilities and investing in new foundational ones. And what is needed depends on whether the business has done any data integrations with sensors before, the volumes and types of data being collected, and whether the business opportunities around IoT are customer facing.


Industries have different experiences with sensors and IoT


There are some organizations that have been digitizing the physical world for some time. They include manufacturing, facilities management, and industrial companies that have historically used sensor technologies to report and control the operational environments. While IoT enables a lot more data and real time collaboration, some businesses in these industries have had a head start in the business, operational, and technology practices that enable using sensor data at scale.

Other industries have sensor data, but opening up this data to consumer facing applications creates new challenges. Many healthcare, entertainment, education, retail, and auto companies fall into this category.

Then there are companies that haven't had must business need for sensor data. Some are in the financial services, media, and professional services industries.

Foundational practices across all industries


Here is my list of key foundational practices all industries need to consider when establishing IoT backed products and services.

  • Data streaming - The ability to collect, process, and manage data in real time. While engineers will focus on the volume and velocity of data when considering data infrastructure requirements, a more important design consideration is what types of decision making, analytics, or algorithms need to run in real time. This leads to questions around algorithm selection, edge computing capabilities, and sensor reliability.
  • Business and technology partnering - IoT requires stitching together technologies and services from multiple business and technology partners. It isn't something you just send to the IT group to architect and assemble. For many organizations, selecting the right partners and integration strategies will stretch their existing vendor, architecture, integration, and procurement practices. 
  • Data security - For many organizations, data security was largely about protecting enterprise data assets behind firewalls and in managed data center and cloud environments.While some IoT is deployed on enterprise networks and facilities like in manufacturing and industrial use cases, others are in more open environments. In addition, since much of IoT is delivered through vendor devices, third party technologies, and vendor services, having a security practice that can evaluate the end to end platform for data security and other risks represents a new set of challenges.
All this means is that many organizations will have to invest in foundational capabilities before bringing new IoT backed product and services to production.



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