Category: Database

In this post, we use dbt for data modeling on both Amazon Athena and Amazon Redshift. dbt on Athena supports real-time queries, while dbt on Amazon Redshift handles complex queries, unifying the development language and significantly reducing the technical learning curve. Using a single dbt modeling language not only simplifies the development process but also automatically generates consistent data lineage information. This approach offers robust adaptability, easily accommodating changes in data structures.

This post explores how you can use BladeBridge, a leading data environment modernization solution, to simplify and accelerate the migration of SQL code from BigQuery to Amazon Redshift. BladeBridge offers a comprehensive suite of tools that automate much of the complex conversion work, allowing organizations to quickly and reliably transition their data analytics capabilities to the scalable Amazon Redshift data warehouse.

This is the final part of a three-part series where we show how to build a data lake on AWS using a modern data architecture. This post shows how to process data with Amazon Redshift Spectrum and create the gold (consumption) layer.

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze your data using standard SQL and your existing business intelligence (BI) tools. Tens of thousands of customers today rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it […]

We’re excited to announce the general availability (GA) of Amazon DynamoDB zero-ETL integration with Amazon Redshift, which enables you to run high-performance analytics on your DynamoDB data in Amazon Redshift with little to no impact on production workloads running on DynamoDB. As data is written into a DynamoDB table, it’s seamlessly made available in Amazon Redshift, eliminating the need to build and maintain complex data pipelines.

While the potential of generative artificial intelligence (AI) is increasingly under evaluation, organizations are at different stages in defining their generative AI vision. In many organizations, the focus is on large language models (LLMs), and foundation models (FMs) more broadly. This is just the tip of the iceberg, because what enables you to obtain differential […]

In this blog post, we will highlight how ZS Associates used multiple AWS services to build a highly scalable, highly performant, clinical document search platform. This platform is an advanced information retrieval system engineered to assist healthcare professionals and researchers in navigating vast repositories of medical documents, medical literature, research articles, clinical guidelines, protocol documents, […]

In this post, we walk you through the process of testing workload isolation architecture using Amazon Redshift Data Sharing and Test Drive utility. We demonstrate how you can use SQL for advanced price performance analysis and compare different workloads on different target Redshift cluster configurations.

In this post, I’ll walk you through how to copy data from one Amazon Relational Database Service (Amazon RDS) for PostgreSQL database to another, while scrubbing PII along the way using AWS Glue. You will learn how to prepare a multi-account environment to access the databases from AWS Glue, and how to model an ETL data flow that automatically masks PII as part of the transfer process, so that no sensitive information will be copied to the target database in its original form.

Kaplan, Inc. provides individuals, educational institutions, and businesses with a broad array of services, supporting our students and partners to meet their diverse and evolving needs throughout their educational and professional journeys. In this post, we discuss how the Kaplan data engineering team implemented data integration from the Salesforce application to Amazon Redshift. The solution uses Amazon Simple Storage Service as a data lake, Amazon Redshift as a data warehouse, Amazon Managed Workflows for Apache Airflow (Amazon MWAA) as an orchestrator, and Tableau as the presentation layer.