Remove Cost-Benefit Remove Data Architecture Remove Data Warehouse Remove Structured Data
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Exploring real-time streaming for generative AI Applications

AWS Big Data

Both engines provide native ingestion support from Kinesis Data Streams and Amazon MSK via a separate streaming pipeline to a data lake or data warehouse for analysis. Data streaming enables you to ingest data from a variety of databases across various systems.

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Your Data Architecture Holds the Key to Unlocking AI’s Full Potential

CIO Business Intelligence

In order to move AI forward, we need to first build and fortify the foundational layer: data architecture. This architecture is important because, to reap the full benefits of AI, it must be built to scale across an enterprise versus individual AI applications. Constructing the right data architecture cannot be bypassed.

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How GamesKraft uses Amazon Redshift data sharing to support growing analytics workloads

AWS Big Data

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

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

AWS Big Data

The following diagram illustrates the different pipelines to ingest data from various source systems using AWS services. Data storage Structured, semi-structured, or unstructured batch data is stored in an object storage because these are cost-efficient and durable.

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Leverage Data Virtualization to Build a Modern Data System

CDW Research Hub

As organizations grow and evolve, many find a need for more sophisticated analytics across an ever-increasing amount of digital and consumer data. But most legacy data architectures do not have a unified data model, and they are hard-wired toward specific BI tools that do not support self-service analytics.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

The data volume is in double-digit TBs with steady growth as business and data sources evolve. smava’s Data Platform team faced the challenge to deliver data to stakeholders with different SLAs, while maintaining the flexibility to scale up and down while staying cost-efficient.