That early hype eventually led to a maturing market and big data is now a proven reality with IDC forecasting sales to reach $187 billion by 2019. That’s quite a staggering amount especially when you compare it to Gartner’s estimate of the Business Intelligence and Analytics market being $16.9 billion in 2016.
Nowadays, there’s a whole new set of technology trends which are dominating the technology landscape similar to the way big data dominated things just a few years ago. You know what I’m referring to: hot trends like Internet of Things (IoT), Artificial Intelligence (AI) and Machine Learning (ML). Gartner does a nice job of plotting these trends in their annual Hype Cycle for Emerging Technology report.
So what does this all mean as it relates to the business intelligence market? First, it’s important to clarify what each of these concepts are since there’s often confusion.
According to this Business Insider article, Internet of Things can be defined as “A network of internet-connected objects able to collect and exchange data using embedded sensors.” For me, the easiest way to make it real is hearing about actual customers who have successfully deployed IoT solutions. There are more and more business intelligence IoT case studies popping up but here are a few interesting ones:
- Rentokil Initial: Leading pest control company deployed connected digital sensor devices to deliver new levels of proactive risk management against the threat of pest infestation – for instance, mapping weather patterns with rodent behavior or tracking swarms of insects as they cross territories.
- British Gas: Leading utility company has deployed over one million smart meters and is targeting 16 million by 2020. The data lake contains more than nine billion records and takes in data from sources including over 150 SAP tables. British Gas managers can now find out “what the company isn’t doing well and can change”.
- Mesur.IO: Innovative agriculture industry startup who places sensors to correlate and measure water consumption, irrigation patterns and weather impact. This enables cost savings related to reduced water usage and also helps conserve resources through automatic ordering of fertilizer, seed and water.
Mike Saliter - Qlik Blog