Nowadays, 85% of the data collected are small datasets approximating one thousand entries. Small Data represents the bulk of data created each year, which is why Small Data Analysis is essential.
The number of data produced worldwide is continuously increasing. It should double every 6 years ! Being bigger and bigger, this data is becoming more complex to assess, prepare, interpret and secure. Plus, most of the data generated is unused. Every department : Marketing, Sales, Manufacturing, Research & Development, Tests, Quality Insurance is generating valuable data on a daily basis. But this data remains untreated.
Small Data is generated by every sensor in the world: wether by manufacturing, by healthcare researchers, by industrial equipment maker, by smart cities, etc. In fact, 85% of the data collected are small datasets.
Generated by highly skilled teams during their daily processes, Small Data often collects the core information of a company’s business and can be used to control and monitor operations within each departments. It’s a key asset to most companies.
Structured with few rows of data, with less variables than Big Datasets, Small Data are easy and cheap to collect, to store and to manage. Being processed by the company which produces them, these data are less prone to tampering meanwhile being easier to interpret.
With big data you can afford to have noise that you filter out. With small data everything is meaningful.
Small Data Analysis is the core of MyDataModels technology. It allows machine learning software with a light footprint to run directly on constrained IoT devices. Easy and agile, it moves intelligence closer to where it is really needed, where action happens locally.
Yet Small Data have a problem: they are very difficult to use for traditional machine learning or artificial intelligence.
Precisely analyse Small Data Analysis in a matter of seconds and building very good prediction models from your Small Data, with no data expertise can sound tricky.
MyDataModels allows you to use your data to build predictions in the cloud if you wish to, or to embed a predictive model software in your equipment, even the smallest of microcontrollers.
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