In the last few years, analytics has evolved significantly. We’ve moved from the adoption of big data technology that was all about Hadoop and Spark, to an increased focus on machine learning algorithms, deep learning and artificial intelligence (AI).
In the last year alone, I’ve noted a renewed hype around machine learning, which together with the Graphics Processing Unit (GPU) evolution is bringing innovation to the marketplace. In general, this ‘new wave’ of machine learning and AI is being adopted much faster than the old wave of Hadoop and Spark. To some, Hadoop and Spark are already becoming legacy.
In this timeframe, I’ve had the pleasure to work with clients across the globe, which has allowed me to see how innovation progresses differently in different places. For a number of years now, companies have been combining software engineering with very advanced machine learning capabilities and applying analytics operations frameworks. It’s quickly becoming widely accepted that advanced machine learning should be part of any data science practice to help customers solve business problems through things like advanced deep learning techniques.
In the fast moving space, North America, the UK and Germany, and the Nordics are the leaders in innovation currently, with the rest of Europe slightly lagging behind. Looking at Asia, it’s fascinating to see that China and Japan are focusing on AI – they lead the results when you Google “countries adopting machine learning.”
From an industry-specific perspective, adoption does vary from sector to sector, but one thing remains the same – when we speak to market leaders and senior management, such as CTOs and chief analytics officers, they all identify AI as a top agenda item. I’d say that by 2020, every company will be seeing AI as a top 5 issue for their business strategy, whatever the sector.