IoT will continue to drive the collection and analysis of larger , more complex data .
PART 3
Data Governance & Modeling for IoT
By Joey Jablonski
Traditional technology platforms will continue to evolve in order to support the Internet of Things as data volumes and velocity increase . This evolution will enable data to be collected from a multitude of different sources , with various standards , as well as time-centric data in collection and analysis . IoT by definition ensures that data is collected and analyzed in a reliable manner , helping users to make more informed decisions .
Through the proliferation of sensors , mobile devices and connected electronics , IoT will continue to drive the collection and analysis of larger , more complex data to be collected and analyzed , while enabling more personalized user interactions .
Data Governance
With of the volume and complexity of the data associated with IoT platforms , mature Data Governance programs must be adopted as part of the data collection and analysis process . Effective Data Governance includes :
• Data Quality Standards – All IoT platforms should have a defined set of data standards that are enforced through rules in the workflow , which are then executed in Dataflow . Data quality standards ensure that recommendations and predictive models receive quality input and poor quality data is discarded .
• Data Retention Standards – As IoT platforms grow , the amount of data will continue to increase . All data retention policies should consider the time value of data when determining the length of retention . IoT platforms should include automated methods for the removal of unnecessary data .
• Data Privacy Standards – All IoT solution designs should begin with an assessment of data privacy specific to the types of data it receives . This assessment should then be used to create application standards in order to guarantee that the data is only accessed by authorized and access audited users .
IoT will continue to drive the collection and analysis of larger , more complex data .
Data Modeling
In addition to Data Governance , IoT platforms require flexible data models supported through reliable data platforms . IoT environments use the Data Model to enable performance to be optimized for the chosen platform . Reliable platforms ensure data is
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