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Amazon OpenSearch Service launches flow builder to empower rapid AI search innovation

AWS Big Data

This middleware consists of custom code that runs data flows to stitch data transformations, search queries, and AI enrichments in varying combinations tailored to use cases, datasets, and requirements. Ingest flows are created to enrich data as its added to an index. Flows are a pipeline of processor resources.

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Streamline AI-driven analytics with governance: Integrating Tableau with Amazon DataZone

AWS Big Data

You can now use your tool of choice, including Tableau, to quickly derive business insights from your data while using standardized definitions and decentralized ownership. Refer to the detailed blog post on how you can use this to connect through various other tools.

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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. But first, let’s define what data quality actually is. What is the definition of data quality? Why Do You Need Data Quality Management?

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Accelerate your data workflows with Amazon Redshift Data API persistent sessions

AWS Big Data

You can create temporary tables once and reference them throughout, without having to constantly refresh database connections and restart from scratch. This enables you to integrate web-based applications to access data from Amazon Redshift using an API to run SQL statements. Building a serverless data processing workflow.

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Ingest data from Google Analytics 4 and Google Sheets to Amazon Redshift using Amazon AppFlow

AWS Big Data

With Amazon AppFlow, you can run data flows at nearly any scale and at the frequency you chooseon a schedule, in response to a business event, or on demand. You can configure data transformation capabilities such as filtering and validation to generate rich, ready-to-use data as part of the flow itself, without additional steps.

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Modernize a legacy real-time analytics application with Amazon Managed Service for Apache Flink

AWS Big Data

Key performance indicators (KPIs) of interest for a call center from a near-real-time platform could be calls waiting in the queue, highlighted in a performance dashboard within a few seconds of data ingestion from call center streams. Visualize KPIs of call center performance in near-real time through OpenSearch Dashboards.

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BMW Cloud Efficiency Analytics powered by Amazon QuickSight and Amazon Athena

AWS Big Data

The CLEA dashboards were built on the foundation of the Well-Architected Lab. For more information on this foundation, refer to A Detailed Overview of the Cost Intelligence Dashboard. Data providers and consumers are the two fundamental users of a CDH dataset.