Censuses have long provided governing authorities with data that helps them make decisions affecting the lives and livelihoods of people everywhere. In modern times, however, companies look for more than just a name when doing business—and that’s where master data comes in. Find out how your
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
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
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.
Spreadsheets are excellent tools as far as they go—but how far can they truly go? If you’re pushing your spreadsheet-based solutions beyond their viable limits, then they might be doing more harm than good. Discover what considerations you shouldn’t ignore when using spreadsheets for statistical
The complexity of multiple data sources contributing to the rising tide of data has executives at many enterprises up at night because of concerns involving risks, regulations and compliance. See why information governance is especially vital in today’s complex ecosystem of voluminous data sources
Over the past two years IBM has been moving in the direction of being a data driven cognitive and cloud company. As part of this transformation, IBM has acquired The Weather Company that provides some of the most accurate weather data to pinpoint the impact of impending weather event to a specific
Data analytics is no longer an either/or choice. With the integration of IBM SPSS Statistics and R, you can bring together the statistical analysis and data management capabilities that have helped so many data scientists gain insight after insight from their data.
The combination of Jupyter Notebooks, Apache Hadoop and Apache Spark has become a killer app for data practitioners. It unlocks the ability to explore, visualize and experiment with both structured and unstructured data sets with great ease and efficiency. We spoke recently with Chris Snow at IBM
Apache Spark, sometimes called the “analytics operating system,” is empowering organizations of all kinds through machine learning by helping them create unprecedented value from their data. Discover eight ways that Apache Spark’s machine learning capabilities are driving the modern business.
Beat the database migration status quo by adopting IBM Bluemix Lift, a self-service ground-to-cloud database migration offering that you can use to boost the speed, reliability and security of your database migration.