Semantic ETL for Real Time Big Data Analytics
What’s the link between the trends of more and more objects and even commercial transactions on the web being described in a machine-readable, semantic format and the endless streaming of all that data?
Newscaster
First Retail Newscaster™ is a lightweight content discovery solution for semantic search within news articles. It can be configured to work against real-time newsfeeds and published media, enabling business teams to find recent and relevant content to deliver quickly and directly to customers.
Analysts Should Be Analyzing, Not Searching
News is a highly perishable commodity. With the speed of information today, global events can have significant market impact in minutes. The most successful analysts have access to the right information at the right time, and can leverage it to competitive advantage.
First Retail Newscaster analyzes millions of news articles and content items from internal and external sources, structured or unstructured, tagged or not, and determines their relevance to a specific concept or topic. It matches them to a given keyword query or even another article, automatically curating and returning the most relevant ones.
With Newscaster, analysts can quickly and efficiently discover critical information in near real-time, freeing them to spend their time sifting value from the global content stream instead of spending time searching it.
Simple Implementation and Deployment
- Newscaster is available as an installed application or as a cloud-based SaaS implementation.
- Can be deployed against existing newsfeeds or a pre-configured Associated Press newsfeed.
- Available with standard user interface or a custom designed interface that works with your proprietary information portal.
- The technology is proven to scale to corpora consisting of millions of documents.
For more information about how your organization can leverage the power of Newscaster, contact us today.