What is an accelerator?
Understand added value of weather data
How weather impacts business
Achieve financial success
Help organizations to understand which products need to be promoted by the store and weather conditions for an upcoming marketing campaign or upcoming inventory planning session
Understanding how weather conditions can directly impact sales in particular store locations or for specific products
Determine where the most revenue uplift exists when doing marketing or inventory forecasting
End-to-end AI Ladder application
An architecture enabling you to extract meaning from your data
From cataloging data through a glossary of terms to model development and deployment, simplify the lifecycle of your AI project
Composable and extensible pattern that can be applied to new data and industries
IBM Cloud Pak for Data
Built on Red Hat OpenShift Container Platform, IBM Cloud Pak for Data accelerates your journey to AI to transform how your business operates with an open, extensible data and AI platform that runs on any cloud.
Watson Knowledge Catalog
Help your data users quickly find, curate, categorize and share data, analytical models and their relationships with other members of your organization.
Empower your data science and AI teams to refine data and visually build and deploy models, using data on the desktop for anytime, anywhere access.
IBM Knowledge Accelerators
IBM Knowledge Accelerators offer pre-created, extensive, curated glossaries to improve data classification, regulatory compliance, self-service analytics and other governance operations.
You can use SPSS Modeler flows to build machine learning pipelines that you can use to iterate rapidly during the model building process.
Sales Prediction using The Weather Company Data
Use machine-learning models and The Weather Company data to help you predict how weather conditions impact business performance, for instance prospective sales.
Manufacturing Analytics with Weather
Use The Weather Company data to help you understand how a manufacturer can quickly identify the reasons why there are high amounts of scrap rate to save money and deliver quality product. This demonstration shows how weather was the key driver leading to reducing scrap rate using statistical analysis and dashboards using Cloud Pak For Data (CP4D).