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Centralize near-real-time governance through alerts on Amazon Redshift data warehouses for sensitive queries

AWS Big Data

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud that delivers powerful and secure insights on all your data with the best price-performance. With Amazon Redshift, you can analyze your data to derive holistic insights about your business and your customers.

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Simplify your query performance diagnostics in Amazon Redshift with Query profiler

AWS Big Data

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that lets you analyze your data at scale. Amazon Redshift Serverless lets you access and analyze data without the usual configurations of a provisioned data warehouse. Choose a query to view it in Query profiler.

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Business Intelligence Dashboard (BI Dashboard): Best Practices and Examples

FineReport

With the advent of Business Intelligence Dashboard (BI Dashboard), access to information is no longer limited to IT departments. Every user can now create interactive reports and utilize data visualization to disseminate knowledge to both internal and external stakeholders.

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Financial Dashboard: Definition, Examples, and How-tos

FineReport

In today’s dynamic business environment, gaining comprehensive visibility into financial data is crucial for making informed decisions. This is where the significance of a financial dashboard shines through. What is A Financial Dashboard? You can download FineReport for free and have a try!

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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. Sample AWS CDK template This post provides a sample AWS CDK template for a dashboard using AWS Glue observability metrics.

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Achieve near real time operational analytics using Amazon Aurora PostgreSQL zero-ETL integration with Amazon Redshift

AWS Big Data

and zero-ETL support) as the source, and a Redshift data warehouse as the target. The integration replicates data from the source database into the target data warehouse. Additionally, you can choose the capacity, to limit the compute resources of the data warehouse. For this post, set this to 8 RPUs.

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Unlock insights on Amazon RDS for MySQL data with zero-ETL integration to Amazon Redshift

AWS Big Data

The extract, transform, and load (ETL) process has been a common pattern for moving data from an operational database to an analytics data warehouse. ELT is where the extracted data is loaded as is into the target first and then transformed. ETL and ELT pipelines can be expensive to build and complex to manage.