See Amazon Redshift » Sample Database for details. The database is a star schema with two fact tables (sales, listings) and five dimension tables (events, dates, venues, categories, and users). The sample database is the Amazon Redshift TICKIT database, which tracks sales activity for a fictional website where users buy and sell tickets online for music concerts and theater shows. For example, the request “tell me the increase in inventory last month” could be translated to “select sum(item_qty) from inventory where month(received_date) = 10”.īIBot has been integrated with a typical relational database intended for business intelligence and reporting applications. BIBot can respond to user questions about data in a database, by converting the questions into backend database queries, and transforming the result sets into natural language responses.
#Amazon chime bot how to#
This blog post shows you how to use Amazon Lex to implement a business intelligence (BI) chatbot, which we refer to as “BIBot,” although you can customize it to use a different name. By allowing users to explore datasets by asking a series of questions, and maintaining a conversational context, we can provide a whole new experience and relationship with data.
With Amazon Lex, we can bring this same level of convenience to data. Increasingly, people are opting to interact with a bot when they need an answer to a question, to set a reminder, or to obtain a product or service. They are untethering people from keyboards and smartphone gestures by replacing those interfaces with a more natural style of interaction: the spoken word. Conversational interfaces are transforming the way people interact with software applications and services.
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