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Learning Resources for Using Third-Party Data in the Cloud
Expand your knowledge on third-party data so you can discover, subscribe to, and use the right third-party data sets that drive innovation across your organization.
This workshop will provide attendees with a comprehensive understanding of how organizations can use third-party data to accelerate their data analytics pipeline and how data enrichment enables advances problem-solving, reduces resource constraints, and improves business intelligence.
As April 22 is Earth Day, the AWS Open Data team wanted to highlight some new datasets from our geospatial and environmental communities of practice. AWS works with data providers to democratize access to data by making it available to the public for analysis on AWS; develop new cloud-native techniques, formats, and tools that lower the cost of working with data; and encourage the development of communities that benefit from access to shared datasets.
Discover how AWS Data Exchange helps streamline the traditional data ingestion process, allowing data teams to quickly get valuable insights and evolve their business intelligence initiatives.
This workshop will provide attendees with a comprehensive understanding of how businesses are leveraging third-party financial data from AWS Data Exchange to enhance the insights they can gain to help make informed decisions quickly using cloud-based technology and get data-driven insights to help achieve their business outcomes.
In this blog, we will show you how to create a catchment area analysis.A catchment area analysis enables you to gain insights into the relationship between points of interest and the populations that they capture.
This blog discusses various data sharing options and common architecture patterns that organizations can adopt to set up their data sharing infrastructure based on AWS service availability and data compliance.
This workshop will provide attendees with a comprehensive understanding of how businesses are leveraging AWS Data Exchange for Amazon Redshift and Foursquare Studio to gain a competitive advantage, make better decisions, and drive growth. Attendees will learn about the various ways that Foursquare's Places (Point of Interest) data can be used for market analysis and obtaining location-based intelligence via AWS Data Exchange and Foursquare Studio. Through hands-on exercises, attendees will analyze existing market and competitors' footprints, in conjunction with population and demographic data, to uncover the economic value of a location.
Understand how businesses are leveraging AWS Data Exchange for Amazon Redshift and Foursquare Studio to gain a competitive advantage, make better decisions, and drive growth.
In this three-part series, we demonstrate how to transform and prepare IMDb data to power out-of-catalog search for your media and entertainment use cases.
In this post, we walk you through how to apply our trained KG embeddings in Amazon S3 to out-of-catalog search use cases using Amazon OpenSearch Service and AWS Lambda.
As a subscriber, you can find and subscribe to thousands of products from qualified data providers. Data managed via Amazon Simple Storage Service (S3) and Redshift are easily available for use across a variety of AWS analytics and machine learning services. Anyone with an AWS account can be an AWS Data Exchange subscriber.
In this lab, you will learn how to do a one-time data export of the product to which you have subscribed. After you have subscribed to the product, you can export data based on your needs:
In this lab, you will learn how to trigger a custom Lambda function when an entitled data set receives a new revision.
Many providers update products regularly by creating and publishing new revisions to the underlying data sets. In addition to setting up an automatic export to a destination Amazon S3 bucket, subscribers can invoke custom workflows to handle these updates.
Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
You can set up AWS Glue crawlers that can scan data in multiple types of repositories, classify it, extract schema information from it, and store the metadata automatically in the AWS Glue Data Catalog.
Amazon Athena is an interactive query service that makes it easy to analyze data directly in Amazon Simple Storage Service (Amazon S3) using standard ANSI SQL. With a few actions in the AWS Management Console, you can point Athena at your data stored in Amazon S3 and begin using standard SQL to run ad-hoc queries and get results in seconds.
