Remove product connectors
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Enhancing Search Relevancy with Cohere Rerank 3.5 and Amazon OpenSearch Service

AWS Big Data

For financial services firms, this means more accurate matching of complex queries with relevant financial products and information. For e-commerce businesses, they can improve product discovery and recommendations, potentially boosting conversion rates. Every connector is specified by a connector blueprint.

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Bigeye Enable Monitoring, Quality and Lineage of Data

David Menninger's Analyst Perspectives

As a result, many data teams were not as productive as they might be, with time and effort spent on manually troubleshooting data-quality issues and testing data pipelines.  As I previously explained , although data quality and data observability are closely related and complementary, they are separate product categories.

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Scaling RISE with SAP data and AWS Glue

AWS Big Data

Customers can now use the AWS Glue SAP OData connector to extract data from SAP. The SAP OData connector supports both on-premises and cloud-hosted (native and SAP RISE) deployments. AWS Glue OData connector for SAP uses the SAP ODP framework and OData protocol for data extraction. For more information see AWS Glue.

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Simplify data integration with AWS Glue and zero-ETL to Amazon SageMaker Lakehouse

AWS Big Data

To address these challenges and accelerate innovation, AWS Glue has recently expanded its third-party application support by introducing native connectors for 19 applications. This allows data analysts, data engineers, and data scientists to quickly explore ingested data and develop data products that meet the needs of business teams.

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.

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Migrate from Amazon Kinesis Data Analytics for SQL to Amazon Managed Service for Apache Flink and Amazon Managed Service for Apache Flink Studio

AWS Big Data

About the author Julian Payne is a Principal Product Manager at AWS. He is passionate about building products and features to help customers innovate using real-time data processing applications in the cloud. If you need more help, you can ask questions in re:Post , making sure to tag Kinesis Data Analytics for SQL.

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Bridging the gap between mainframe data and hybrid cloud environments

CIO Business Intelligence

Bringing mainframe data to the cloud Mainframe data has a slew of benefits including analytical advantages, which lead to operational efficiencies and greater productivity. These tools dont have the necessary connectors, metadata relationships, or lineage mapping that spans both mainframe and cloud environments.