Remove Big Data Remove Data Warehouse Remove Metadata Remove Visualization
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SAP Datasphere Powers Business at the Speed of Data

Rocket-Powered Data Science

Content includes reports, documents, articles, presentations, visualizations, video, and audio representations of the insights and knowledge that have been extracted from data. We could further refine our opening statement to say that our business users are too often in a state of being data-rich, but insights-poor, and content-hungry.

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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. Looking at the Skewness Job per Job visualization, there was spike on November 1, 2023.

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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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What is a data architect? Skills, salaries, and how to become a data framework master

CIO Business Intelligence

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. Data architect vs. data engineer The data architect and data engineer roles are closely related.

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Use Apache Iceberg in your data lake with Amazon S3, AWS Glue, and Snowflake

AWS Big Data

Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time. Apache Iceberg offers integrations with popular data processing frameworks such as Apache Spark, Apache Flink, Apache Hive, Presto, and more.

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How Morningstar used tag-based access controls in AWS Lake Formation to manage permissions for an Amazon Redshift data warehouse

AWS Big Data

We realized we needed a data warehouse to cater to all of these consumer requirements, so we evaluated Amazon Redshift. At the same time, we had to find a way to implement entitlements in our Amazon Redshift data warehouse with the same set of tags that we had already defined in Lake Formation.

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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

This dynamic tool, powered by AWS and CARTO, provided robust visualizations of which regions and populations were interacting with our survey, enabling us to zoom in quickly and address gaps in coverage. Figure 1: Workflow illustrating data ingesting, transformation, and visualization using Redshift and CARTO.