Internet of Things (IoT) brings with it a massive amount of detailed data and analyzing it is key. This slide deck explores the requirements of IoT analytics and how you can build a solution for it using WSO2's 100% open source analytics platform.

1. Analytics and the Internet of
Things

2. Big data vs. IoT data
● Big data came mostly from computer-based systems whereas IoT
data comes from the natural world through sensors.
● IoT data is more detailed, fuzzy, and large.

3. Requirements of an IoT system
● How fast do you need the results? In a few hours (MapReduce),
seconds (streaming analytics) or milliseconds (complex event
processing)?
● How much data do you need to keep? All the data, none of the data or
a summarized version of the data?

4. Requirements of IoT analytics
● Autocorrelation when processing time series data
● Spatiotemporal analysis and forecast
● Anomaly detection

5. How to act on IoT data
● Visualize the results
● Detect problems and notify the user
● Carry out independent actions with open control loops
● Continuously monitor and control the environment or the underlying
process in a closed control loop

6. Different types of IoT use cases
● Stationary dot: monitoring an already deployed system in operation
● Moving dot: understanding and controlling the behavior of a system

7. What kinds of analysis do you need
from an IoT analytics solution?
● Batch analytics: process historical data that’s collected over a period
of time all at once
● Streaming analytics: process real-time data that is time-sensitive in a
continuous manner
● Predictive analytics: process historical and real-time data to create
machine learning algorithms and models to perform predictions

8. WSO2 Analytics Platform

9. Keep Pace with Innovation
Find out how you can create an efficient IoT analytics solution with WSO2
IoT Analytics: Using Big Data To Architect IoT Solutions