Data is one of the few commodities that is infinite. But while we’ll never run out of data, do you really know how much data you get for 5GB? Or how 2GB of data can be bigger than 5GB of data?
As data get’s bigger, Things get smaller
How much data is 10GB? What can I do with it, and how much will I need? These are all things you’ll need to know before you buy a hard drive, a memory card, a data contract, a SIM card, or choose a tablet or computer based on the memory size. To put it into context, 1TB has the ability to store 1498 CD-ROM discs of data or approximately 130,000 digital photos.
The original 1956 IBM hard drive had a memory capacity of 4MB and needed a forklift to lift it’s ton of weight. Since then, memory capacity of storage devices has increased, while physical size has decreased drastically. A 256 GB smartphone in your pocket has a memory capacity equivalent to 54 Olympic-sized swimming pools completely filled with 1958-era hard drives.
Today we’re dealing with huge data capacities in tiny physical spaces.
So, how big is Big Data?
Big is relative, and ‘Big Data’ is no exception. So, what do we mean when we talk about Big Data in IoT?
For my participation in this year’s RideLondon100, Pangea launched ‘The Big Data Cycle’ where an IoT device on my bike not only tracked my progress during the 100-mile ride through London and Surrey, but also the air quality of the route in which I travelled. The data is collected and transmitted at each data point from the bike every 10 seconds. I had also had the device collecting data during my training rides over the course of 2 months, during in which I rode around 1000 miles.
While that seems like a lot of data, in actuality, only 150 bytes of data is being transmitted at each data point, giving a total data collection of only 4MB—equivalent to one hi-resolution photo on an iPhone. Furthermore, the ride on race day itself only generated a mere 270KB (a two page A4.doc file).
But it’s not the amount of data that’s important. Small data can be Big Data.
Instead, it’s all about how useful that data is—how innovative processing of that data can provide the opportunity for insightful analysis leading to optimised and efficient processes, value added services, automated decision making, enhanced user experiences, and reduced costs, to name a few.
And often, this is where IoT adds real value, with 81% of businesses say IoT delivers real value through the data it generates (Vodafone 2016 Barometer). In this respect, 2GB of data generated by IoT can be Big Data, while the data on 5GB desktop hard drive might not be.
For the Big Data Cycle, the data becomes big when patterns in air quality and athletic training are identified to inform and improve council and training initiatives.
Data for IoT
I said it was important to get the context in the understanding of data size. Now we have the context, how can we make our understanding more useful and relevant? Obviously the more data you buy the more it costs, so nothing new there, and the same goes for IoT. But in IoT there are three key differences:
- The relationship between price and volume is not linear and IoT data is productised in a very different way from data for consumers’ mobile devices. Different partners will have data products built to suit the specific sector. The ‘per-MB pricing model’ makes sense for the device on my bike, but wouldn’t work for the outdoor film production company streaming HD video on a 4G-WAN.
- Management and monitoring of the connection and data (in real time) should be a must have for the partner to ensure the end-user has flexibility to fit their use case.
- If the first two points are done properly and intelligently the end-user can avoid the nightmare of a bill-shock through overage charges.
Often, end users are adamant that they need xxMB, and will later find themselves coming back to revise the scale of data they need.
There is no set formula or look-up table for data in IoT, so a clear understanding at the outset is key to making the delivery frictionless. If you choose the right partner with that understanding, the partner will be able to model the appropriate data, service, and management according to the end users needs. This might include pooling the data, or aggregation of the SIMs to share data across multiple SIMs. A partner that truly understands IoT data and has the flexibility to create the most relevant data package that’s appropriate to the use case, will make a significant difference to the commercials and thereby ensure the success of the project.
If you need help with working out how much data you need, turning that data into Big Data, or would like to find out more about our IoT solutions and partnering with Pangea then please get in touch here.