AI is unlocking tremendous value for businesses by solving many last-mile automation problems that previous waves of technology could not address. But just like any technology early in its evolution and application, there are a few things to watch out for – and unintended bias tops the list. Proper design and rigorous planning can mitigate the issue.
Data engineers are vital members of any enterprise data analytics team, responsible for managing, optimizing, overseeing and monitoring data retrieval, storage and distribution throughout the organization.
Because so much of the location data gathered to gauge foot traffic at restaurants, car dealerships or other business locations is gleaned via mobile apps, several variables can affect the validity of measurement models. Yet, most investors, money managers and consultants are unaware of the risks that lurk when providers of this alternative data fail to update their data models.
One of the biggest challenges faced by organizations when implementing any type of enterprise service management strategy is with the process alignment and people. The recent World Cup tournament teaches us a thing or two about improving your service management efforts.
Forty-eight percent of respondents to a West Monroe survey cited using technology to disrupt incumbents as one of their top drivers for making health care acquisitions. Here’s a look at what they’re buying.
A year into an investigation into the use of data analytics in political campaigns, the U.K.’s privacy watchdog is hitting companies that shared data with political parties with sanctions including a criminal prosecution and a US$660,000 fine.
Jones Lang LaSalle has hit on a successful formula for its leased properties, leveraging mobile apps, IoT and analytics to offer digital services to corporate employees accustomed to personalized services.
The emerging alternative data category, which includes things as diverse as mobile location visit data and corporate air travel data is growing in popularity. Investors and others watching companies in auto, retail and other industries have begun incorporating these unique data sets into the pools of data they use to inform investment decisions. Here's why sophisticated investors are going alternative.
Although it’s widely believed that high-quality data is readily available and accessible, that is not always the case – it is more common, however, in regions with three common attributes. Dan Adams, Vice President of Data Product Management, Pitney Bowes explains the evolving nature of data and more specifically, data visualization’s impact on business purchases.
As a few companies race to monetize the kind of machine learning that focuses on teaching robots to behave more like humans, many companies are grappling with how to leverage artificial intelligence and smart machines.
The NBA's defending champions are using chatbots, augmented and virtual reality to bolster fan engagement. Now they're sifting through fan data to better target them with merchandise, tickets and other offers.
As a CIO, the only constant is change, new requirements, new demands and less budget. This article looks at the factors a successful CIO will need to embrace to be successful in this new age of instrumentation where everything has a digital heartbeat and the ultimate success or failure of the company rests on the CIO.
Over the next year, the traditional enterprise will become the intelligent enterprise – able to detect regulatory, technological, market and competitive challenges and proactively turn them into business successes or opportunities.
Toys ‘R’ Us is shutting its doors, meaning consumers will begin looking elsewhere for their toy needs. Meanwhile, retailers of all shapes and sizes are clamoring to grab Toys 'R' Us’ market share. Location data could uncover insights into who could win the “toy wars.” Location affinity data and analysis gives us clues and could be used by the Walmarts, Amazons and Disney Stores of the world to make smarter decisions about how they approach tomorrow's toy market.
Gone are the days of relying on weather data alone to increase your operational decision-making. Instead, the most successful companies are merging weather data with other information to innovate the way they analyze risk and reward.
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