Targeting Revenue
Analytics in IoT can facilitate companies to understand the preferences and choices of their
customer base. Doing this can improve the oers and services of the company in accordance
with consumer expectations. As a result, profits and revenues can receive a much-needed boost.
Edge
Currently, IoT as a standalone solution is more of a buzzword. Many IoT providers and devel-
opers are continuously trying to beat others and make sure that they are the top names in the
IoT space. Analytics can encourage companies to provide better service and thus oer them an
opportunity to race ahead of others.
For IoT, data analytics is further split into the following categories.
Streaming Analytics
It processes large in-motion data. It analyzes real-time data streams for the detection of quick
issues and comes up with timely decisions. For instance, trac analysis, fleet tracking, and finan-
cial transactions are some of the examples of streaming analytics in IoT. This analytics is also
called as event stream processing.
Spatial Analytics
It is used to look up for geographic patterns in order to assess the spatial relationship among
multiple physical objects. Smart parking applications and other IoT use cases that run on the
back of location-based infrastructure commonly use these analytics.
Time Series Analytics
It processes data on the basis of time in order to determine the relevant patterns and trends for
the current applications. For example, health monitoring systems and weather forecasting are
some of the applications where IoT takes advantage of the analytics.
Quick Challenge
Give one real-life example of IoT implementation where Time Series analytics is useful.
Prescriptive Analysis
The prescriptive analysis is a mix of both predictive and descriptive analysis. It is implemented
to determine those procedures which can help in certain scenarios. IoT applications in the com-
mercial sector often use prescriptive analysis.
There exists a wide range of examples where the IoT applications were able to improve
through data analytics. Technological modifications and advancements allow users to work
with trendy areas which really need IoT and data analytics. For example, data analytics can
be used for actionable marketing. Likewise, IoT analytics have improved the surveillance and
safety of the entire IoT ecosystem.
Healthcare is yet another leading sector in the country. If analytics is used correctly
in healthcare applications, then it can open a new set of possibilities. Analytics can help to
improve monitoring, decrease healthcare costs, and remove health services and boost treat-
ment and diagnosis.
130 Internet of Things
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