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.Analytics Insights: Top 10 worst business intelligence implementation practices to avoidBusiness intelligence (BI) is transforming the workloads of global businesses across multiple industries. BI practices have become one of the key elements to help in decision-making processes to meet customer satisfaction. BI implementation practices can help companies to have a competitive edge in the global tech market companies and the combination of Artificial Intelligence and BI is helping companies to make better and smarter decisions with automation. But it isn’t a fool proof process. We’ve highlighted a few of the worst business intelligence implementation practices to avoid:Collection of poor-quality dataGood quality data is the most important element in business intelligence to integrate into an artificial intelligence model. Poor-quality data will hamper the entire data management process and affect the usefulness of processes such as data harmonisation. Not providing training for BI practicesFor BI practices to be effective, they must be carried out in a standardised consistent manner. Employee training is crucial to ensuring all employees have a proper understanding of business intelligence and artificial intelligence. Making inaccurate estimatesMaking inaccurate estimates can cause delays, hinder the business process and profit in the long term. As well as leading to serious consequences around the project scope. Read more here. Science Daily: How Big Data can help us to better understand cancerous mutationsThe best way of identifying what type of cancer mutation a patient has is to compare one sample from the tumour and one from healthy tissue from the same patient. But these tests can be complicated and costly, so researchers have created a new method – to look for common cell mutations that tend to be benign, in massive public DNA databases so that they can identify rarer mutations that have the potential to be cancerous.University of Colorado Cancer Centre member Ryan Layer, PhD knew that detection of complex DNA mutations called structural variants (SV) can frequently result in false negatives, so he and his colleagues developed a process that focuses on verification instead of detection. This method searches through raw data from thousands of DNA samples for any evidence supporting a specific structural variant. By working out what variants are unique to the tumour, tumour treatment can become super-personalised.Ryan Layer said: ‘Identifying the genetic changes that cause healthy cells to become malignant can help doctors select therapies that specifically target the tumour.’Layer’s lab has now deployed a website where doctors can enter information on structural variants found in a patient tumour to see how common, and potentially dangerous, they are.Read more here.World Economic Forum: How to avoid artificial intelligence bias with ‘responsible AI’Responsible Artificial Intelligence (AI) has become the subject of much discussion in recent years, with trustworthy AI fast becoming an expectation. AI presents transformative opportunities across numerous industries but requires regulation and oversight to match. Having a clear AI governance framework based on clear principles will ensure that AI is used responsibly and optimally for an organisation. AI organisations, have identified the top 5 best practices critical to achieving responsible AI governance, here are just a few to keep in mind: Set out AI PrinciplesIn the first instance, an established set of AI principles must be established that everyone can align with, such as the management team. Leaders also must prompt discussions around the use of AI to ensure it aligns to the company mission and values.Establish a responsible AI governance frameworkDiscussions between numerous parties should be encouraged in order to establish a framework to guide future AI use and to shape AI culture. Heads of innovation can share how they develop and use AI in key functions. HR heads can share where AI is used, whilst general counsel can reflect on potential liabilities in crisis lawsuits. There are an increasing number of frameworks available to help guide management’s efforts.TrainingTo ensure that employees are all on the same page, organisations should provide AI ethics courses to explain principles and obligations in a consistent way. There is also the option of enrolling senior executives in the Responsible AI Badge certification programme which focuses on implementing best practices.Read more about AI governance here.Tech Crunch: Amazon has a new physical retail analytics serviceAmazon is launching a new physical retail store analytics service that offer brands insights about the performance of their products, promotions and ad campaigns. The new service, Store Analytics, will be used in Amazon Go and Amazon Fresh stores that use Just Walk Out and Dash Cart technologies.The ‘Just Walk Out’ technology uses a combination of cameras, sensors, computer vision techniques and deep learning to allow customers to shop, then leave the store without waiting in line to pay. The company says the new service will give brands access to information about how their products are discovered, considered and purchased, which will then help them make informed decisions about campaigns. It will also provide performance metrics for in-store campaigns, such as digital signage.Brands will also be given access to anonymised data about how their products rank and perform. Amazon insists that it will not share anything that can be linked back to individual shoppers.Read more about the new service 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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