AI and machine learning combined with ever-increasing amounts of data are changing our commercial and social landscapes. A number of themes and issues are emerging within these sectors that CIOs need to be aware of.
Future of Big Data- I’ve just spent a couple of days at O’Reilly’s Strata Data Conference in London and got a much better idea where the world of big data, machine learning (ML) and AI may be heading. These sectors have developed rapidly over the last 5 years with new technologies, processes and applications changing the way organisations are managing their data.
The Strata conference provides a good barometer of what the state-of-the-art is in big data manipulation as well as the concerns of developers and users. Eight key points emerged for me from the event.
1. 5G will stimulate the growth of ML and result in new applications and services
I spoke with O’Reilly’s Chief Data Scientist and Strata organiser, Ben Lorica about this and he sees the increased bandwidth and flexibility of 5G as well as the move to edge computing as key enablers. He pointed out that China is a leading global force in this technology but that many firms are still working out the business models for all the 5G investments they are making.
2. Changing skillsets for data scientists
Cassie Kozyrkov, Google Cloud’s chief decision scientist, pointed out in her talk that as the UX for ML tools is improved, the skills required will become less technical and more focused on the ability of data scientists to work across silos and be more integrated into the business.
3. The online and offline worlds are merging
China’s Alibaba ecommerce group and Amazon are experimenting with physical store spaces while bricks and mortar stores are still adapting to the new online world. It feels to me that the offline moves by ecommerce groups are offensive while the online investments by physical retailers are defensive. There is still a long way to go before this fully plays out but the expertise that companies like Amazon and Alibaba have with managing data at scale gives them a key advantage.
4. Internal data platforms are becoming essential for growth and innovation
Presentations from data scientists at Lyft and BMW showed how putting data platforms at the centre of new product development and business process management are driving innovation. While this may come naturally for digitally native companies like Lyft it is also something that traditional, industrial companies are having to engage with as data generating sensors become embedded within products.