Shipping to data: The case of Amazon Prime Day
Did you ever wonder how retail hallmarks like Amazon Prime Day and global shipping are connected? Freightos has the data to answer such questions, as it happens to be on a mission to disrupt the freight industry.
Read More →NBA analytics: Going data pro
For the NBA, like every other sports league, awards are important. They can generate attention, spur debate, make money, and involve fans, players, and experts, among others. Is there data science and analytics behind them — can there or should there be? We picked the NBA Most Improved Player award as an example to analyze some aspects of data-driven culture.
Read More →Advertising data going forward: Transparency and scale
The problem with advertising data and what to do about it. Plus, the future of big data architecture, and other stories from the Ad Tech trenches
Read More →Planet analytics: big data, sustainability, and environmental impact
What is the relation between big data applications and sustainability? What is the net effect of improved efficiency versus increased resource consumption, who gets to measure this, and how?
Read More →Language agnostic document processing: Finding relations using statistics, machine learning, and graphs
Would you like to be able to find related work regardless of domain or language, more efficiently than you ever thought possible? Omnity is out to help achieve this, using a mix of techniques.
Read More →Data Works, Hadoop 3.0 is round the corner, and ‘Horton Hatches the Egg’
What's coming in Hadoop 3.0? How is Hortonworks' strategy evolving? And what are some examples of open-source powered innovation in big data use cases?
Read More →Big Data versus money laundering: Machine learning, applications and regulation in finance
Could financial fraud such as the Laundromat be avoided by applying machine learning to scan through data? And if yes, why is that not happening?
Read More →Disrupting insurance: data-driven customer value
Why hasn't the insurance business been disrupted yet, and how could data be used to do this? Atidot has a go at addressing those questions.
Read More →Googling prescriptive analytics: YouTube recommendations and the analytics continuum
Understanding prescriptive analytics is complicated, let alone implementation. Would turning to Google help? Seeing how it works for Google raises questions, but may also lead to some answers.
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