Converting real-time weather data into business intelligence
Humans have been building weather forecasts for millennia. What started as cloud-watching in ancient Babylonia became science in the 19th century, informed by thermometers, barometers and the telegraph. A century later, radar, satellites and computers ushered in the modern forecasting era. The past three years have seen a great leap forward thanks to an explosion of weather sensor data—much of it from mobile phones. This data deluge, coupled with the rise of cloud computing and data analytics technologies, has brought unprecedented advances in forecasting accuracy, and businesses are beginning to capitalize on it. Highly precise and near-real-time forecasts are helping businesses such as insurance companies reduce damage claims, retailers optimize staffing and packaged goods companies sell more shampoo.
This Internet of Things podcast explores how IBM and The Weather Company are working together to help deliver an average 15 billion forecasts a day to 2.2 billion locations around the globe to benefit all kinds of industries. The Weather Company is drawing business intelligence from something once considered inherently unpredictable, the weather, and enabling businesses everywhere to convert weather data into a competitive advantage.
What’s more, the rise of mobile, real-time data, cloud computing and the vastly improved forecasts have forced The Weather Company to rethink its business model. Using these technologies, The Weather Company has evolved the way it operates. It delivers more than just weather bulletins; it offers business intelligence to clients in insurance, government, retail, and the energy and utilities sectors. As a result, it is becoming faster and more nimble even as it manages an ever-growing tsunami of data, equivalent to terabytes of data every hour.
To learn more, listen to the podcast How Businesses Everywhere are Benefiting from a Deluge of Weather Data. Tune in for a new episode of the Wild Ducks podcast series on the last Thursday of every month. To receive the podcast episodes automatically, subscribe on iTunes or SoundCloud.