Data Warehousing

How to Manage Data Retention in AWS Data Warehouses: Best Practices for Compliance and Efficiency

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Managing data retention in AWS data warehouses is an essential practice for ensuring that your organisation’s data remains organised, secure, and cost-effective. By establishing clear data retention policies, you enable your data warehouse to serve its purpose without becoming cluttered with obsolete information. AWS provides a suite of tools designed to streamline the data retention …

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How to Design a Data Warehousing Schema for Optimal Performance on AWS: Key Strategies and Best Practices

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Designing a data warehousing schema on AWS requires an understanding of both the technical capabilities of AWS services and the principles of data warehousing architecture. The goal is to structure your data in a way that supports efficient storage and rapid retrieval, facilitating complex analytics and business intelligence tasks. With AWS, you have access to …

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How to Use AWS Glue for Aurora PostgreSQL Data Transformation and Redshift Optimization Techniques

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Migrating data from Amazon Aurora to Amazon Redshift requires effective strategies to transform and optimise data for analytics processing. AWS Glue, a fully managed extract, transform, and load (ETL) service, facilitates this process by preparing and loading your data for analytics. By understanding how to configure Aurora PostgreSQL as a source and effectively design ETL …

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How to Use AWS Glue Data Catalog with a Data Warehouse: Integrating for Enhanced Data Management

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Using the AWS Glue Data Catalog with a data warehouse facilitates a comprehensive approach to data management, ensuring that your data is not only well-organised but also easily accessible for analysis and business intelligence tasks. The AWS Glue Data Catalog serves as a central repository where metadata—pertaining to the structure, location, and runtime metrics of …

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How to Use AWS Lake Formation Blueprints for Efficient Data Ingestion from Aurora PostgreSQL to Redshift

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When managing large volumes of data, efficient ingestion processes become pivotal for businesses leveraging cloud platforms. AWS Lake Formation simplifies this by providing blueprints, which are predefined templates for common data loading tasks. If you’re working with Aurora PostgreSQL and need to move data to Redshift, using Lake Formation blueprints can streamline the process. Understanding …

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How to Build a Resilient Data Warehousing Architecture with Aurora PostgreSQL and Redshift: A Comprehensive Guide

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Building a resilient data warehousing architecture is pivotal for businesses that rely on quick and accurate data analysis for decision-making. With Aurora PostgreSQL and Redshift, combining the performance and reliability of Aurora with the analytics capabilities of Redshift can provide a solid foundation for your data warehousing needs. Aurora PostgreSQL is a fully managed relational …

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