Amazon Redshift

Auto Added by WPeMatico

Build a conversational data assistant, Part 1: Text-to-SQL with Amazon Bedrock Agents

Advanced (300), Amazon Bedrock, Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, Amazon QuickSight, Amazon Redshift, Artificial Intelligence, Best Practices /

What if you could replace hours of data analysis with a minute-long conversation? Large language models can transform how we bridge the gap between business questions and actionable data insights. For most organizations, this gap remains stubbornly wide, with business teams trapped in endless cycles—decoding metric definitions and hunting for the correct data sources to […]

Build a conversational data assistant, Part 1: Text-to-SQL with Amazon Bedrock Agents Read More »

Query Amazon Aurora PostgreSQL using Amazon Bedrock Knowledge Bases structured data

Amazon Aurora, Amazon Bedrock, Amazon Bedrock Knowledge Bases, Amazon Redshift, Intermediate (200), Technical How-to /

Amazon Bedrock Knowledge Bases offers a fully managed Retrieval Augmented Generation (RAG) feature that connects large language models (LLMs) to internal data sources. This feature enhances foundation model (FM) outputs with contextual information from private data, making responses more relevant and accurate. At AWS re:Invent 2024, we announced Amazon Bedrock Knowledge Bases support for natural

Query Amazon Aurora PostgreSQL using Amazon Bedrock Knowledge Bases structured data Read More »

Choosing the right approach for generative AI-powered structured data retrieval

AI/ML, Amazon Bedrock, Amazon Bedrock Knowledge Bases, Amazon Machine Learning, Amazon Q Business, Amazon QuickSight, Amazon Redshift, Amazon SageMaker, Amazon SageMaker AI, Generative AI, Generative BI, Natural Language Processing /

Organizations want direct answers to their business questions without the complexity of writing SQL queries or navigating through business intelligence (BI) dashboards to extract data from structured data stores. Examples of structured data include tables, databases, and data warehouses that conform to a predefined schema. Large language model (LLM)-powered natural language query systems transform how

Choosing the right approach for generative AI-powered structured data retrieval Read More »

Build conversational interfaces for structured data using Amazon Bedrock Knowledge Bases

Advanced (300), AI/ML, Amazon Bedrock Knowledge Bases, Amazon Redshift, AWS Glue, Generative AI, Technical How-to /

Organizations manage extensive structured data in databases and data warehouses. Large language models (LLMs) have transformed natural language processing (NLP), yet converting conversational queries into structured data analysis remains complex. Data analysts must translate business questions into SQL queries, creating workflow bottlenecks. Amazon Bedrock Knowledge Bases enables direct natural language interactions with structured data sources.

Build conversational interfaces for structured data using Amazon Bedrock Knowledge Bases Read More »

Build generative AI chatbots using prompt engineering with Amazon Redshift and Amazon Bedrock

Advanced (300), Amazon Bedrock, Amazon Redshift, Generative AI, Technical How-to /

With the advent of generative AI solutions, organizations are finding different ways to apply these technologies to gain edge over their competitors. Intelligent applications, powered by advanced foundation models (FMs) trained on huge datasets, can now understand natural language, interpret meaning and intent, and generate contextually relevant and human-like responses. This is fueling innovation across

Build generative AI chatbots using prompt engineering with Amazon Redshift and Amazon Bedrock Read More »