A data scientist uses machine learning (ML) to find heretofore unknown correlations and other patterns in fresh data. ML is adept at finding both the "known unknowns" and the "unknown unknowns" through the power of supervised learning and unsupervised learning methodologies, respectively.
The goal of moving beyond basic TV ratings and simple consumer demographics to establishing a secure analytics environment to integrate subscriber, set-top-box and third-party, enriched data in near real time is something leading media and entertainment organizations continue to embrace. After all
The organization that can quickly extract insight from their data AND leverage the data achieves an advantage. Rick Clements, IBM's director of marketing for Big Data says, "we are moving from the notion of big data to fast data, where what really matters is speed...and real-time actionable insight
IBM InfoSphere BigInsights is an industry-standard Hadoop offering that combines the best of open source software with enterprise-grade features. Let’s talk about some key features of the distribution and the top ten reasons to love it.
Ernst & Young (EY) uses IBM BigInsights platform to leverage big data and analytics to combat fraud. By running test queries across multiple transactions they can identify fraudulent transactions and mitigate risk for its customers.
Today's customer expects businesses to know their specific needs and cater to them. Personalization is no longer a nice-to-have but a must-have. By utilizing big data, companies can gain a deeper understanding of customers and transform the customer experience. Shane Sweeney, head of engineering of
Research from International Customer Management Institute (ICMI) reveals that only 25 percent of companies feel that their customers are "extremely engaged." How, then, can companies increase customer engagement to cultivate fans? Is creating the same passion in customers as sporting teams a myth?
The need for a data scientist is all the rage right now. At every marketing conference I go to, companies are clamoring for their skills, but the supply and demand is not coming to the needed equilibrium. We are faced with the choice of continuing to wait, or to employ a solution that is already at
With the growth of big data and analytics comes additional responsibilities to ensure privacy. Privacy engineering are the tools, use case scenarios and measures to insure that privacy has been designed into your solutions and operational practices.
Leading media and entertainment companies need to stop guessing and start knowing. They need the ability to analyze all available data, from inside and outside the enterprise, as it is generated, in real time, at high velocity. They can no longer wait to analyze data after it’s been processed and
IBM Counter Fraud Management introduces advanced analytics and deep investigative analysis throughout the entire life-cycle of counter fraud operations. This enables organizations to aggressively handle fraudulent activity while pro-actively anticipating, preventing and continuously adapting to