Category: Amazon Redshift
In this blog post, we demonstrate joining data from Snowflake with data shared from a third party provider via AWS Data Exchange in Amazon Redshift. This solution lets you access and combine data from all these resources without needing to build and maintain complex data pipelines.
Spatial data is a key ingredient for many analytical use cases, such as route optimization, location-based marketing, asset tracking, or environmental risk assessment. Bulk geospatial tasks like geocoding and generating isoline polygons have traditionally required complex APIs or highly specialized software—not to mention the Extract Transform Load (ETL) processes involved in those approaches. CARTO has […]
In this blog post, I will show how data-driven organizations can easily integrate third-party data products procured via AWS Data Exchange into your data mesh using the new AWS Data Exchange for AWS Lake Formation feature.
In this blog post, Jeff, Mike, and I will show you how to discover and use no-cost open data datasets on AWS Data Exchange. We will also show you how to enrich the open data with a paid dataset and how to import these datasets into Amazon SageMaker and do an analysis against them.
In an article this summer, Harvard Business Review made a strong case for the importance of artificial intelligence (AI) in today’s business world. According to HBR, AI technologies are “poised to have a transformational impact, on the scale of earlier general-purpose technologies” (i.e., databases or the internet). But the fact that these technologies will soon […]