Internet of Things (IoT) Data Analytics
The Internet of things (IoT) has generate a huge amount 'buzz' in the last couple years. If you have this on your resume it would have given you much street cred. When someone says he or she does IoT, it is almost like back in 90s someone saying I work on the internet. To better understand (IoT) we need to understand its history from early machinery to IoT.
- Human to one Machine - Radios, Early Analog Machine
- Human with one machine - Laptops, Desktop
- Human to Multiple Machines - Networks, Internet
- Human to machine to machine back to Human - Internet of Things or Internet of Everything
With the growth of the internet and networks and now Internet of things, data growth has been rapid in the last couple years. Many companies are facing petabytes of data. Now what is next? Just for your education.
With more data gathered by smart devices and communicated through a faster network, the growth of data has become a blessing and also a curse. Every company has data issues. Either it is data retention, data cleansing, data integration or data analytics. Congratulations, you are not alone. We can not target it all in one blog post, but lets focus on what is the purpose of the data. The purpose of data is to create an action that will improve the business. This action needs to have use case. Let's circle back to IoT use cases.
All IoT use cases fall under two areas:
- Information Analytics
- Automation and Control.
To give you some of idea of the varied use cases across a cross-section of industries, we have prepared a White Paper entitled "Internet of Things (IoT) Data Analytics" to help you envision how you might put some of this river of data to use within your business. Just click to download it.
Out of the five IoT component levels, the most recognition goes to Devices, Network and Analytics. What is a IoT Device? If you own a Smart phone or a car, congratulations, you own a IoT device! What is a network? Internet, Bluetooth, anything else associated with communication. What is analytics? Analytics covers a wide variety of solutions, for example, within the big data realm, Hortonworks, Cloudera, and MongoDB are the front runner in Hadoop/Nosql solution provider landscape. Please refer to Fundamental of IoT to have better understanding of the three components.