Abstract

Over time, analytics and information management (AIM) technology adopted for IoT will be different from an organization's existing technology investments that performs a similar, but less time-sensitive or data volume–intensive function. Enterprises will want to leverage as much of their existing AIM investments as possible, especially initially, but will want to adopt IoT-aligned technology as they operationalize and identify functionality gaps in how data is moved and managed, how analytics are applied, and how actions are defined and triggered at the moment of insight. This IDC TechScape covering IoT AIM is designed to help:

  • Enterprises learn more about the newer AIM technologies that support IoT
  • Align these technologies with an enterprise's technology risk profile to determine what is ready to adopt and what should be monitored
  • Gain a better understanding of where an IoT team will need to create skills and competencies as it plans to adopt newer AIM technologies

According to Maureen Fleming, vice president for IDC's IoT Analytics and Information Management research program, "Implementing the analytics and information management tier of an IoT initiative is about the delivery and processing of sensor data, the insights that can be derived from that data and, at the moment of insight, initiating actions that should then be taken to respond as rapidly as possible. To achieve value, insight to action must fall within a useful time window. That means the IoT AIM tier needs to be designed for the shortest time window of IoT workloads running through the end-to-end system. It is also critical that the correct type of analytics is used to arrive at the insight."


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