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Mobility is hardly new in enterprise circles. Businesses are busily building mobile apps for in-house use and for customers, while the task of managing employees' mobile devices absorbs many companies' CIOs. Some organizations, however, look to refine their mobile strategies. When eHarmony reworks its mobile applications, for example, the relationship services provider does so with the backing of a 25TB data warehouse and a roster of data analytics tools. The dating service has spent the last five years building a business intelligence platform. A MicroStrategy -based analytics layer sits atop the data warehouse.
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Online dating is now one of most common ways to meet your significant other; in , Statista found that 45 percent of UK survey respondents were current or past users of Match. Dating apps and websites are big business, and more and more of us are trusting digital means to help us find the one. To what extent do dating sites and apps use big data and machine learning to pair potential new couples? The short answer is that it varies — a location-centric app like Tinder offers matches solely according to their proximity to a set area, while compatibility-focused sites like Match. The fact that Match, a paid-for dating site, was found to be more popular than many of its free of charge counterparts suggests that many users are looking for a more data-led approach to dating.
As of April , one in every eighteen United States citizens are using big data to find a companionship . In the age of online dating, big data analytics has become a major contributor to leading to potential relationship success, because online dating services have to deal with a huge amount of data. As an example, Match. This demonstrates that technology and big data are changing the dating game.