It has been claimed that 90% of data in the world today has been created in the last couple of years alone. Think about that. At 2.5 quintillion bytes of data a day that's a lot of data. So what is happening to all this data and how might it be a driving force behind a variety of future technologies?
From the outset, let us dispel the myth that software, whether relating to big data or otherwise, is unpatentable. It can be challenging but these type of inventions can be patented in the UK and Europe where there is a credible technical effect. This is also possible even if applied to a non-technical field where there is something special about the implementation (think implementations that result in fewer read/write instructions, which utilise parallel processing etc.) For further information on this, in the broader context of software and data, click here for a related article by my colleagues.
What is Big Data?
Big data is the term generally used to refer to extremely large data sets that may be analysed and processed computationally to reveal patterns, trends and associations to gain insights. So, what is an insight? It can mean forming an understanding of something based on data analysis to help make a decision. Some data is structured, i.e. arranged in some sort of known format like a table. Some, most likely the vast majority of this data, is unstructured. Unstructured data is disorganised. However, given that so much of our daily lives involve interaction with something that generates masses of unstructured data, from our phones to our cars, looking into the meaning of both structured and the more mysterious unstructured data using computers can help people and organisations make decisions.
If, for example, we can analyse masses of data at our disposal to work out why people do what they do, what they like and don't like, then we can make decisions and suggestions. This sort of insight can "drive" future policies. Advertisers of course use analytics to work out who to target, and where that targeting converts into sales and where it doesn't. Other applications of big data analysis involve fraud detection, agriculture, banking, transport infrastructure and telecommunications. If we can understand and predict when a telephone network is going to be busy, and why, then we can plan resources accordingly.
The Future
Data scientists are in high demand. Industry and government recognise the value of using big data analytics to form commercial insights and to develop products that meet customer needs and which themselves may function better based on data crunching. With the ever-lowering cost of cloud storage, access to harvested data repositories and proprietary analysis platforms, the sector is growing fast.
In recent times, we have helped protect new IoT devices, ways of anonymising data sets, and new ways of controlling systems based on analytics. Despite the challenges, patent protection is available for many innovations in this sector.
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