Despite undertaking measures to improve data security and privacy, 38 per cent of global organisations responding to a survey say they are still not compliant with the new general data protection regulation (GDPR) requirements.
At a highway check point on the outskirts of Beijing, local police are this week testing out a new security tool: smart glasses that can pick up facial features and car registration plates, and match them in real-time with a database of suspects.
A Netflix-style recommendation engine on steroids, a Google AdWords beater and a souped-up game simulator are among a number of machine learning models at work behind the scenes at online bookmaker Sportsbet, the company has revealed.
The big data market is expected, by one estimate, to grow more than 30 percent annually until the end of the decade. But more than half of big data projects fail--and even those that do succeed can fall apart if the findings aren't applied to operational efficiencies. Ron Bodkin, CEO of Think Big Analytics, offers advice to help you prevent your business from becoming just another statistic.
Making use of the petabytes of patient data that healthcare organizations possess requires extracting it from legacy systems, normalizing it and then building applications that can make sense of it. That's a tall order, but the facilities that pull it off can learn a lot.
In-memory analytics, like virtualization and the cloud, is an old idea that's been given new life. In this case, the combination of big data, inexpensive commodity storage and parallel processing make it possible to analyze terabytes of data without slowing systems to a crawl.
In recent years, big data and artificial intelligence (AI) have received overwhelming attention, however the interesting – even obvious – connection between the two hasn’t often been explored. It is the combination of big data and AI working together that is now enabling business leaders to deliver new insights, efficiencies and even new functions that haven’t been possible before. This is evident in the increasingly useful role big data and AI are playing in a broad spectrum of traditionally outsourced functions such as recruitment, HR, finance and supply chain, through to security and IT.
It should be clear to every IT leader in every industry that data is eating the world. The retail sector is no different. And finding the people who can mine the gold out of the vast veins of data running through the retail world is proving particularly challenging.
1.The concept is still quite new. The term data lake, credited to Pentaho CTO James Dixon, has been bandied about for several years. But the idea of data lakes as corporate resources is still in its infancy, according to IDC analyst Ashish Nadkarni. A data lake is defined as a massive--and relatively cheap--storage repository, such as Hadoop, that can hold all types of data until it is needed for business analytics or data mining. A data lake holds data in its rawest form, unprocessed and ungoverned.
Big Data. Predictive analytics. Real-time. Actionable insight. There's a buzzword smorgasbord around the use of data to derive value. It doesn't help that sometimes the benefits can be esoteric, or at least hard to visualize. But sometimes the benefits are crystal clear, as in the fight against sepsis, one of the leading killers in the US.
This guide reviews how predictive analytics helps your organisation predict with confidence what will happen next so that you can make smarter decisions and improve business outcomes. It is important to adopt a predictive analytics solution that meets the specific needs of different users and skill sets from beginners, to experienced analysts, to data scientists