“The Internet of Things (IoT) is the next technological revolution, expected to generate over $300B by year 2020, according to Gartner. The IoT will also generate unprecedented amounts of data and its impact will be felt across the entire big data universe.”
Kaushik Pal examines the following 4 areas of Big Data landscape impacted by IoT:
Collection of IoT Big Data
Companies try to collect all data related to their businesses. IoT creates big challenges in data processing, maintenance, analysis and security.
Data Security Issues
Data protection in the past is mainly at the enterprise level. But in the age of IoT, hackers can attack things around our private lives.
Identifying Redundant Data
IoT not only generates massive useful data, it generates a lot of messy data as well. It is not easy to Identify and filter out redundant data.
Impact on Daily Lives
Sensor is everywhere. IoT totally re-define our lives. IoT is a benefit when it works for you; but it might be a risk when it works against you.
“Before the Internet of Things (IoT) came along, billions of networked sensors and devices capable of generating enormous amounts of new, unstructured real-time data. Big data was already really, really big. To tackle this, businesses small and large have taken to the cloud and reworked their IT architectures to create more flexible, scalable ways to manage their data.”
IoT makes Big Data even more challenging because IoT generated a lot more data. To overcome these common technical barriers, Carey Wodehouse put together a list of 5 recommendations:
- More data means companies will have to rethink their IT and data center infrastructures.
- With the IoT, quality data will be actionable data.
- NoSQL databases will most likely outpace traditional RDBMSs.
- Beyond collecting data, businesses need to choose a software stack for preprocessing and analyzing IoT data.
- We’ll need more and more skilled data analysts to make IoT data valuable.