Remove Dashboards Remove Data Warehouse Remove Metadata Remove Visualization
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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics, Part 3: Visualization and trend analysis using Amazon QuickSight

AWS Big Data

Grafana provides powerful customizable dashboards to view pipeline health. QuickSight makes it straightforward for business users to visualize data in interactive dashboards and reports. QuickSight makes it straightforward for business users to visualize data in interactive dashboards and reports.

Metrics 103
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Manage your data warehouse cost allocations with Amazon Redshift Serverless tagging

AWS Big Data

Amazon Redshift Serverless makes it simple to run and scale analytics without having to manage your data warehouse infrastructure. Tags allows you to assign metadata to your AWS resources. In Cost Explorer, you can visualize daily, monthly, and forecasted spend by combining an array of available filters.

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How HR&A uses Amazon Redshift spatial analytics on Amazon Redshift Serverless to measure digital equity in states across the US

AWS Big Data

HR&A has used Amazon Redshift Serverless and CARTO to process survey findings more efficiently and create custom interactive dashboards to facilitate understanding of the results. This frees up our local computer space, greatly automates the survey cleaning and analysis step, and allows our clients to easily access the data results.

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Near-real-time analytics using Amazon Redshift streaming ingestion with Amazon Kinesis Data Streams and Amazon DynamoDB

AWS Big Data

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, easy, and secure analytics at scale. Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the widely used cloud data warehouse.

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How to get powerful and actionable insights from any and all of your data, without delay

Cloudera

By enabling their event analysts to monitor and analyze events in real time, as well as directly in their data visualization tool, and also rate and give feedback to the system interactively, they increased their data to insight productivity by a factor of 10. . Our solution: Cloudera Data Visualization.

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Case study: Policy Enforcement Automation With Semantics

Ontotext

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy.

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Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 111