As Internet of Things
applications are evolving, a lot of attention has been put on devices, sensors,
connectivity and data gathering. However, the technology behind the IoT and the
data it generates is outpacing our ability to consume, analyze, and drive value
with it. This must change, organizations need to focus on the necessary data
streams and their possible business enablers first … before implementing any IoT
solution.
Some key considerations to
start with:
- What insights can add value to my business or to my clients’ business
- What extra services can/do we want to offer to our (potential) client-base if we could provide real-time insights
Internet of Things
analytics is a bit of a different animal from business as usual analytics or
even Big Data analytics. Data gathering from Internet of Things applications
can vary depending on the use case. The number of sensors and volumes of data
can range wildly depending on the application but at the core of the Internet
of Things is a tremendous amount of structured data (machine data) coming in at
a high velocity.
“Processing data to provide actionable insights
is what it’s all about ...
it’s not the things that matter ...
it’s processing the data.”
Advanced data management
and analytic infrastructure will be key for an IoT solution. Companies that are
building the data management and analytic component of their IoT applications
on a traditional, monolithic relational database infrastructure will quickly
find that their large scale analytic requirements will break their legacy
architectures and the costs to maintain their architecture will skyrocket.
No comments:
Post a Comment