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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

QuickSight makes it straightforward for business users to visualize data in interactive dashboards and reports. An AWS Glue crawler scans data on the S3 bucket and populates table metadata on the AWS Glue Data Catalog. You can deploy the end-to-end solution to visualize and analyze trends of the observability metrics.

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How Amazon Devices scaled and optimized real-time demand and supply forecasts using serverless analytics

AWS Big Data

To further optimize and improve the developer velocity for our data consumers, we added Amazon DynamoDB as a metadata store for different data sources landing in the data lake. You can visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes.

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Data Insights for Everyone — The Semantic Layer to the Rescue

Rocket-Powered Data Science

They realized that the search results would probably not provide an answer to my question, but the results would simply list websites that included my words on the page or in the metadata tags: “Texas”, “Cows”, “How”, etc. The BI team may be focused on KPIs, forecasts, trends, and decision-support insights.

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Apache Ozone Powers Data Science in CDP Private Cloud

Cloudera

Before we jump into the data ingestion step, here is a quick overview of how Ozone manages its metadata namespace through volumes, buckets and keys. . If created using the Filesystem interface, the intermediate prefixes ( application-1 & application-1/instance-1 ) are created as directories in the Ozone metadata store.

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BMW Cloud Efficiency Analytics powered by Amazon QuickSight and Amazon Athena

AWS Big Data

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. Once released, consumers use datasets from different providers for analysis, machine learning (ML) workloads, and visualization.

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CCPA 2020: Getting Your Data Landscape Ready

Octopai

Octopai’s metadata discovery and management suite provides visualization tools that empower you to see and report everything about sensitive customer data. Octopai's Automated Metadata Management Platform can make CCPA compliance a breeze. Keeping the Lights On with Automated Metadata Management. Not Yet CCPA Compliant?

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How healthcare organizations can analyze and create insights using price transparency data

AWS Big Data

Using machine learning (ML) and data visualization tools, these datasets can be transformed into actionable insights that can inform decision-making. The architecture approach is split into a data intake layer, a data analysis layer, and a data visualization layer. The Data Catalog now contains references to the machine-readable data.