Predictive analytics isn’t complete without geospatial analytics, which offers data dimensions that can provide a holistic view of business problems. At IBM Insight 2015, discover how geospatial analytics can help you understand your customers and your operations through time and space components.
For businesses, there are multiple ways to think about the future; no two companies take the same view when trying to anticipate what’s coming next. However, analytics can accommodate all these unique visions of the future by helping organizations understand their data and glean insight from it.
When it comes to big data and analytics, you can expect the unexpected. A wide range of companies is applying insights in ways that may surprise you. Here are four examples featuring an unusual mix of companies where the only common denominator is their success with analytics.
Today's banking environment and ever-changing digital technologies require financial institutions to embrace banking customer analytics with a new view: understanding customer behavior in a digital world has immense value.
As many organizations are rapidly learning, predictive analytics delivered on cloud-based platforms has the potential to transform the way organizations conduct business. To take advantage of new possibilities, leveraging enterprise-scale, cloud-based predictive analytics for new opportunities
Although predictive maintenance offers significant benefits to personnel who operate and maintain essential assets, its dependence on additional on-premises IT resources can deter organizations from relying on it. Learn how an IBM cloud-based solution can help give organizations insight into asset
Weather can be just as important a factor in retail success as location is. Both by boosting planning efficiency and by mitigating supply chain risk, weather data analytics can help retailers predict and meet customer demand—rain, snow or shine.
Unprecedented opportunities await enterprises that are involved with the Internet of Things—but only if they apply analytics to their production or operational processes with Predictive Asset Optimization. This addition can help prevent costly delays, maximize assets and improve the consumer
As the “tsumani of data and information” flooding organizations threatens to become overwhelming, many companies—particularly telecoms—need a solution that handles enormous data volumes with stellar performance and cost-efficiency. See how one company uses predictive analytics to tame this tsunami
No matter the industry, organizations are increasingly seeing the merits of learning more about their customers to inform the generation of intelligent, targeted offers. Take a look at five key questions commonly heard from executives in a range of industries about establishing predictive customer
Big data and analytics technology is driving business forward, the newest natural resource in the ever-changing world of computing. Yet even in a constantly evolving industry, certain trends stand out. Take a look at what’s on the horizon for big data and analytics, and find out how it could affect
The traditional banking model is changing as fiercer competition and heightened customer expectations of digital banking put the customer experience at the top of the priority list. Banks are leveraging predictive analytics solutions to enhance targeting via customer segments and to provide custom
Why are people talking about Apache Spark? It’s because many organizations are using the myriad features of this open source engine to boost their predictive analytics processing. The result? Better, deeper and faster data analyses with reduced coding time and effort.