The market chatter about Big Data and AI is relentless. For Big Data, the statistics that many of us in the tech industry see bandied about are certainly eye catching; 2.7 Zetabytes of data exist in the digital universe today, 571 new websites are created every minute of the day, by 2020 business transactions on the internet will reach 450 billion per day etc. For AI, they are no less impressive; there was more than $300 million in venture capital invested in AI startups in 2014, a 300% increase over the year before; by 2018, 75% of developer teams will include AI functionality in one or more applications or services; by 2020, 30% of all companies will employ AI to augment at least one of their primary sales processes etc.
However, for many people not directly involved in the tech industry or the IT department of a huge multinational it’s difficult to see how these grandiose claims have any relevance to their day to day tasks. The real issue is, until recently, to do anything innovative with big data or AI you needed highly skilled data scientists versed in seemingly impenetrable technologies like NoSQL, R, MapReduce or Scala. And these guys are hard to come by and expensive, and not getting cheaper. IBM predicts that demand for data professionals in the US alone will reach 2.7 million by 2020.
However, that’s not the complete picture. Much in the same way computers began entering the business world as the preserve of large corporations like J Lyons & Company and the U. S. Census Bureau, were later more widely used as companies that could afford the huge cost of buying them provided services to others, and finally the productization of computers by the likes of IBM allowed almost every organisation to buy their own, Big Data and AI are going through the same process of democratization.
The major three Cloud data providers Microsoft, Google and Amazon are amongst a host of providers that now offer scalable and affordable Big Data platforms that can be spun up in seconds. In the last few years all three have also started offering API driven AI services bound into their cloud platforms. More importantly, those Big Data platforms and AI API’s are now becoming easily accessible to more traditional development environments like .NET. This means that millions of traditional developers can now leverage Big Data and AI without leaving the comfort of their familiar development environment.
The natural consequence of this will be an explosion of products that leverage Big Data and AI technologies available to even the smallest organisations, allowing the huge opportunities to filter down to all. In fact, here at DataPA we have spent the last twelve months working hard on a new automated analytics product leveraging Big Data and AI techniques, which we are hugely excited about launching in the coming months. The world is on the cusp of huge change that historically will rival the industrial revolution, and we are excited about sharing that journey with all our customers and partners in the coming months and years.