Weekly News Digest: 14th – 18th February 2022 | Harnham Recruitment post

This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of Data & Analytics.FORBES: DATA MARKET TRENDS AND PREDICTIONS FOR 2022The challenges faced last year have fostered increased innovation. The pandemic gave rise to digital twins, the metaverse, the omniverse, blockchain, and NFTs (non-fungible tokens). All of which were fueled by Web 3.0 and 5G. So, what is in store for 2022?The Data EconomyThe industry has moved beyond cloud computing, into a data economy. Data fuels AI and AI helps to create actionable insights from the data. Technologies like robotic data automation are a prime example.No code/low code platforms for citizen developersAlthough most businesses now realise the importance of data and AI, implementing data functions can be daunting. It can take around eight months for an AI model to be integrated into a business application. This is where code/low-code platforms can help, by democratising data and AI and making it accessible to non-proficient users. Read further about market predictions here.GOVTECH: HOW DATA AND ANALYTICS CAN HELP COMBAT HUMAN TRAFFICKING IN THE US US State and local government agencies that deliver social services are constantly grappling with troubling issues such as human trafficking. Human trafficking has been able to persist for numerous complex and intertwined reasons, and effective counter-trafficking has been hampered by a lack of reliable information. Social services and police often lack accurate, up-to-date information about the individuals involved in trafficking, where it’s taking place and the co-existing social issues that might signal its occurrence.State, city and local agencies have decided to take the challenge into their own hands, by implementing a purpose-built data-sharing platform to identify, correlate and act on relevant data. Data sharing can bring together information from a variety of relevant agencies such as social services and educational organisations and then be used to create data visualisations, such as graphs and heat maps, to track trends and recognise risk factors. Read more here.RACONTEUR: WHY BETTER DATA GOVERNANCE IS THE KEY TO BETTER AIArtificial intelligence (AI) is everywhere and is helping to tackle numerous business challenges via decision intelligence, machine learning or some other form of AI. It is true that many businesses can indeed benefit from this tech, but only if they take the time to fully understand what it can and can’t do, and any potential pitfalls.Fundamentally, AI allows its users to do useful things with a large pool of data – which makes the quality and quantity of what’s being fed into a machine-learning application directly linked to the accuracy of its output. Data governance is key to ensuring that AI yields useful results. It combines an awareness of ethical and legal issues but also the implications these have for what material must be collected, as well as its potential limitations. Organisations that will benefit most from AI will be those who take the time to build a framework that ensures they are targeting the right amount of data, collating quality data and using it in the correct way. Read more here. INTERESTING ENGINEERING: HOW PROFESSIONAL SPORTS TEAMS ARE HARNESSING DATA SCIENCE TO BRING THEIR A-GAMEMany sports organisations have turned to AI in recent years in search of competitive advantages. Although all professional football teams feature an analytics department, English football club Liverpool FC has decided to take a unique approach. Their analytics teams have built pitch control models to help predict how each action on the pitch would affect the probability of its players scoring a goal while in possession of the ball. To collect the data to power the models, cameras are set up all around the stadium to track the position of the players and the ball. Over the course of one match, analytics teams may end up with as many as 1.5 million data points to process. While pitch models are useful during pre-and post-match analysis, they’re also harnessed in real-time to help inform the team’s game strategy. However, it relies on the players to actually execute the strategy, making it open to numerous variables which can render the analytical model useless. Data Science is also being utilised in basketball games, read how here. We’ve loved seeing all the news from Data & Analytics in the past week, it’s a market full of exciting and dynamic opportunities. To learn more about our work in this space, get in touch with us at info@harnham.com.    

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