The unprecedented expansion of the Internet of Things (IoT) has led to a rapidly expanding amount of generated data. Industry experts are warning that at the current rate of growth, unstructured data will inevitably become an unmanageable tsunami. Data management overload is a near-certainty.
The unprecedented expansion of the Internet of Things (IoT) has led to a rapidly expanding amount of generated data. Industry experts are warning that at the current rate of growth, unstructured data will inevitably become an unmanageable tsunami. Data management overload is a near-certainty.
Citing a recent Gartner report, Enterprise Tech reports that the impact of IoT on enterprise infrastructure will be serious. The report says that “due to a lack of information capabilities adapted for the IoT” an estimated 25% of attempts to use IoT data will have to be abandoned prior to successful deployment.
Gartner also warns that specialists who are responsible for IoT strategies and for managing data governance are not adjusting rapidly enough for the data-driven implications of IoT.
Gartner states that information management must be a key core competency in the near future to avoid disaster. The capabilities of IT managers and others will be challenged by the new governance infrastructure — this will also impact their tools, skills, and traditional processes.
The ability to handle data management overload is crucial.
One of the key requirements for future IoT data management capability is an ability to manage distributed data architecture in a way that executes governance processes while at the same time completely supporting analytics, according to Gartner.
Gartner projects that at least 25% of IoT implementations will have to be jettisoned in early stages, and their report suggests using a framework of information capabilities as an alternate template for organizations battling with the data surge. Such an approach starts by assessing the value of information with metadata analysis, and then moving on to data governance regulations applied across the board. Afterward, the said data can be refined and integrated into a larger enterprise matrix.
A major test for IoT data managers is to reconsider organizational storage limits, plus analyzing the condition users will be able to access in the IoT data system.
This same report also warns that the tide of unstructured IoT data is set to overwhelm existing information storage capacity — which only has a finite expansion ability.
Gartner also predicts a bottleneck will be created if the ability to efficiently scale current storage approaches is not reexamined and modified.
A major information management reassessment is definitely needed.
Because of the highly variegated nature of most IoT data consumption and generation, the report also advised IT managers to reassess their reliance on conventional centralized data pools.
Since IoT basically functions at the three-phase commit protocol level (3PC), Gartner concludes that because of the diverse design mandated for IoT solutions, the traditional approach to consolidated data collection is under intense scrutiny. And changes are definitely coming. Wanted or not.