Remove Big Data Remove Data Warehouse Remove Interactive Remove Structured Data
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Build an Amazon Redshift data warehouse using an Amazon DynamoDB single-table design

AWS Big Data

These types of queries are suited for a data warehouse. The goal of a data warehouse is to enable businesses to analyze their data fast; this is important because it means they are able to gain valuable insights in a timely manner. Amazon Redshift is fully managed, scalable, cloud data warehouse.

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Build a decentralized semantic search engine on heterogeneous data stores using autonomous agents

AWS Big Data

For getting data from Amazon Redshift, we use the Anthropic Claude 2.0 To get data from Amazon OpenSearch Service, we chunk, and convert the source data chunks to vectors using Amazon Titan Text Embeddings model. For client interaction we use Agent Tools based on ReAct. This is unstructured data augmentation to the LLM.

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Data governance in the age of generative AI

AWS Big Data

First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses. The user permissions are evaluated using AWS Lake Formation to filter the relevant data.

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The rise of the data lakehouse: A new era of data value

CIO Business Intelligence

Traditionally, organizations have maintained two systems as part of their data strategies: a system of record on which to run their business and a system of insight such as a data warehouse from which to gather business intelligence (BI). That’s how we got here.

Data Lake 139
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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

Customer 360 (C360) provides a complete and unified view of a customer’s interactions and behavior across all touchpoints and channels. This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. Then, you transform this data into a concise format.

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Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS

AWS Big Data

Apache Hive is a distributed, fault-tolerant data warehouse system that enables analytics at a massive scale. Spark SQL is an Apache Spark module for structured data processing. Note: -Your query environment must have the Hive Client tool installed and a connection to your Hive metastore or AWS Glue Data Catalog.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.