Essentially, Monte Carlo simulations predict an outcome not from the actual values of input data (which aren’t known) but from the likely (aka “simulated”) values of that data (based on their probability distributions). These simulations can prove invaluable for assessing risks in many real-world
Consumers want everything on demand because virtually anything is one click away from their smartphones. See how the race is on for marketers to give customers what they want, when and where they want it by unleashing the power of data, analytics and cognitive computing to redefine the customer
Although spreadsheets offer a stable, attractive option when working with numbers, they can fall far short when they are applied to enterprise-scale statistical analytics. Weigh the limitations of spreadsheets against the benefits of a sophisticated, enterprise-grade statistical analysis tool for
The Internet of Things continues to be a land of opportunity in so many areas. Take a look at this overview of steps to innovation and success factors along with the risks and pitfalls to avoid in your Internet of Things journey.
Open source tools continue to foster non-stop innovation throughout the Insight Economy. So it’s no surprise that open-source languages—most notably, R--have moved to the center of enterprise statistical analytics and data management.
IBM Watson Customer Insight for Insurance helps you leverage dynamic customer segmentation to create a more personalized policyholder experience based on the policyholder's financial and life events. This video demonstrates how to view and share actionable insights from easy-to-use, customizable
Nick Pentreath of the Spark Technology Center teamed up with Jean-François Puget of IBM Analytics to deliver the main talk of the Spark & Machine Learning Meetup in Brussels, "Creating an end-to-end Recommender System with Apache Spark and Elasticsearch."
At the recent Spark & Machine Learning Meetup in Brussels, Holden Karau of the Spark Technology Center delivered a lightning talk called "A very brief introduction to extending Spark ML for custom models."
At the Spark & Machine Learning Meetup in Brussels on October 27, 2016, Pierre Borckmans of Real Impact Analytics delivered a lightning talk called "Writing Spark applications, the easy way: How to focus on your data pipelines and forget about the rest."
Big data and design thinking share some common core principles for creating highly connected, meaningful business and customer user experiences. See why organizations worldwide are realizing the magic of combining big data with design thinking to generate value for powerful business use cases.
Do you find yourself increasingly having to make decisions amid uncertain conditions? The advanced capabilities offered by IBM SPSS Statistics aim to make Monte Carlo simulation a part of your risk analysis by bringing these two worlds together in a single software solution.