AWS Marketplace
Category: Analytics
Simplify AWS Marketplace activity visualization with a single pane of glass
In this post, Ramya and I introduce you to the new SPG dashboard as a single pane of glass for your Marketplace transactions. You can view this dashboard without having AWS Identity and Access Management (IAM) permissions or technical proficiency on the underlying AWS services. We show how you can use the SPG dashboard for a simplified view of your AWS Marketplace subscriptions for spend management and usage tracking.
Building a real-time recommendation engine with Amazon MSK and Rockset
In this post, we demonstrated how to build a real-time product recommendation engine by leveraging the fully managed streaming capabilities of Amazon MSK, along with the real-time analytics and SQL capabilities of Rockset.
Food supply chain optimization using PredictHQ intelligent event data from AWS Data Exchange for demand forecasting
In this post, we will show how it may be possible to avoid wastage and better forecast food needs using PredictHQ’s dataset with Amazon Forecast and other machine learning services.
Accelerate self-service analytics integrating on-premises and third-party data with AWS Data Exchange and Dremio
In this blog post, we explore how businesses can use AWS Data Exchange with their on-premises Hive-compliant data source using Dremio to integrate third-party and on-premises data without moving or copying data. We also demonstrate how customers can use the consolidated data for business intelligence (BI) and exploratory analytics.
Join third-party data in Amazon Redshift with Snowflake using Amazon Athena
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.
Quant research at scale using AWS and Refinitiv data
In this blog post, Alex, Pramod, and I will show how to install and use the infrastructure we built to perform quant research at scale. We made the stack and examples available in the public repository so you can use it in your own investment research. This solution uses Apache Spark, Amazon EMR on EKS, Docker, Karpenter, EMR Studio Notebooks, and AWS Data Exchange for Amazon S3.
Masking Patient Data with DataMasque’s template for Amazon HealthLake
In this post, Brian, Snehanshu, and I’ll show you how to mask healthcare data for regulatory compliance using Amazon HealthLake and DataMasque.
Database auditing with DataSunrise Security in AWS Marketplace
In this post, Juston and I will show you how to make an automated data access report using the DataSunrise application for Aurora PostgreSQL-Compatible Edition.
Create catchment areas using drive times with Redshift and AWS Data Exchange
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 […]
Accelerating Spark workloads on Amazon EMR with Windjammer’s Spark plugin
AWS customers often use Apache Spark for distributed big data processing. Spark has gained popularity due to its fast in-memory computing that enables parallel computation of tasks across multiple nodes. To aid customers with running Spark workloads, Amazon EMR provides a managed cluster platform that makes it easy to run frameworks such as Apache Hadoop, […]