Remove Data Architecture Remove Data Lake Remove Optimization Remove Structured Data
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Detect, mask, and redact PII data using AWS Glue before loading into Amazon OpenSearch Service

AWS Big Data

Leadership and development teams can spend more time optimizing current solutions and even experimenting with new use cases, rather than maintaining the current infrastructure. With the ability to move fast on AWS, you also need to be responsible with the data you’re receiving and processing as you continue to scale.

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Databricks’ new data lakehouse aims at media, entertainment sector

CIO Business Intelligence

The other 10% represents the effort of initial deployment, data-loading, configuration and the setup of administrative tasks and analysis that is specific to the customer, the Henschen said. Features focus on media and entertainment firms. Partner solutions to boost functionality, adoption.

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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. For more details, refer to Create a low-latency source-to-data lake pipeline using Amazon MSK Connect, Apache Flink, and Apache Hudi.

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The hidden history of Db2

IBM Big Data Hub

In today’s world of complex data architectures and emerging technologies, databases can sometimes be undervalued and unrecognized. Store and query more than just traditional structured data with multi-model capabilities. To learn more, visit IBM Db2 and our IBM data management page. .

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

CIO Business Intelligence

Businesses that lead in fully deploying AI will be able to optimize customer experiences and efficiencies that help maximize customer retention and customer acquisition and gain a distinct advantage over the competition. In order to move AI forward, we need to first build and fortify the foundational layer: data architecture.

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Migrate a petabyte-scale data warehouse from Actian Vectorwise to Amazon Redshift

AWS Big Data

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. The architecture consists of many layers: Rules engine – The rules engine was responsible for intercepting every incoming request.

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Get maximum value out of your cloud data warehouse with Amazon Redshift

AWS Big Data

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. This performance innovation allows Nasdaq to have a multi-use data lake between teams.