Machine data is all around us: logs, sensors, GPS devices and meters to name a few. The enormous growth of machine data has become a major driver of big data solutions and a challenge for many organizations. The complex and diverse nature of machine data leaves many organizations unable to leverage
This infographic highlights key findings from the 2014 report titled “Pushing the frontiers: CFO insights from the global C-Suite study,” which draws input from nearly 4,200 of C-suite executives representing more than 20 industries. Learn more about the insights behind the study in this podcast.
Scientists from IBM are collaborating with John Hopkins University and University of California, San Francisco to combat illness and infectious diseases in real-time with smarter data tools for public health by applying the latest analytic models, computing technology and mathematical skills on an
IBM data scientists break big data into four dimensions: volume, variety, velocity and veracity. This infographic explains and gives examples of each.
For additional context, please refer to the infographic Extracting business value from the 4 V's of big data.
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Aberdeen has long illustrated the benefits of well-managed, trustworthy data, and the problems associated with poor data quality. As data volumes rapidly expand and data environments become more complex, what were once small nuisances evolve into massive, company-wide problems. In order to avoid
IBM software and expertise analyzes more than 41 million data points to determine the top three "Keys to the Match" for Grand Slam tennis tournaments. That same predictive analytics technology is used every day by leading organizations to solve their most pressing business challenges.
See how "The Big Datastillery," a revolutionary new “appliance,” condenses terabyte-scale torrents of customer, transactional, campaign, clickstream and social media data down to meaningful and actionable insights that boost response rates, conversions and customer value.