The trend towards digital transformation of the enterprise, regardless of industry or sector, will accelerate in 2017 from the already significant levels seen last year. We identify the following seven digital technology trends as game changers for software-driven enterprises. The crumbling of the barriers to entry for machine intelligence – driven by the availability of high-quality open-source software components; cloud platforms from all major providers; and the availability of wildly popular and high-quality introductory courses on MOOC platforms – will drive growing mainstream adoption of machine intelligence as a differentiating and foundational technology layer in the digital transformation stack for identifying and closing new revenue opportunities, customizing user experience, driving operational efficiencies, and predicting failures. Also expect to see acceptance and greater adoption of advanced machine learning techniques for delivering closed-loop actionable insights in domains such as the Industrial Internet of Things and cybersecurity. The fully distributed, transparent, tamper-resistant, and auditable shared ledger technology known as blockchain is particularly powerful in settings where multiple parties need to reconcile without a central intermediary, or need to track provenance of assets across organizational boundaries, or need to establish and enforce contracts between untrusting parties and speed up reconciliation with a secure and verifiable audit trail.
So today we focus on helping companies learn faster and better understand trends in customer behavior. After assessing its needs and analyzing user behavior, we helped them create a mobile app that integrated web functionality with mobile. Forget downloading apps: With Google's Instant Apps, your smart device leads you only to that part of the app that you need to perform a specific task. A year ago, Nasdaq introduced Nasdaq Linq, its blockchain ledger technology to help companies complete and record private security transactions.
A British artificial intelligence firm is looking to revolutionise the world of sports transfers by designing software that picks out bargain rugby players. ASI Data Science has signed a deal with London Irish, the rugby union club, to help it find undiscovered gems by using cutting edge data analysis techniques. While rugby scouting typically requires looking through hours of footage to assess a player's ability, the software allows a club to enter the name of a star player and will assess match statistics to find players with similar styles. It looks through around 100 different parameters taken from Opta, the sports data company, which covers every professional player on the planet, to find players similar to the star that a club would buy if money were no object. The machine learning software clusters different types of players together, making it easier for scouts and analysts to find players and removing the biases that many believe cloud judgements when signing players.
Cardiff Metropolitan University is a thriving University based in the capital city of Wales with around 12,000 students and a further 6,000 transnational education students across the world. Cardiff Met was rated the top post 1992 university in the REF 2014. A full-time Data Science position is available to support a collaborative research project between Cardiff Metropolitan University and World Rugby. The project aims to; examine the subsequent injury risk following concussion in professional Rugby Union players, and to develop an associated software analysis tool using machine learning. This is an exciting opportunity to be involved in a collaborative project between Cardiff Metropolitan University and World Rugby.