AWS Big Data Blog

Category: Analytics

How GE Healthcare modernized their data platform using a Lake House Architecture

GE Healthcare (GEHC) operates as a subsidiary of General Electric. The company is headquartered in the US and serves customers in over 160 countries. As a leading global medical technology, diagnostics, and digital solutions innovator, GE Healthcare enables clinicians to make faster, more informed decisions through intelligent devices, data analytics, applications, and services, supported by […]

Visualize data using Apache Spark running on Amazon EMR with Amazon QuickSight

Organizations often need to process large volumes of data before serving to business stakeholders. In this blog, we will learn how to leverage Amazon EMR to process data using Apache Spark, the go-to platform for in-memory analytics of large data volume, and connect business intelligence (BI) tool Amazon QuickSight to serve data to end-users. QuickSight […]

Build a centralized granular access control to manage assets and data access in Amazon QuickSight

A large business intelligence (BI) project with many users and teams and sensitive information demands a multi-faceted security architecture. Such architecture should provide BI administrators and architects with the capability to minimize the amount of information accessible to users. For a straightforward solution to manage Amazon QuickSight user and asset access permissions, you can use […]

Calculated fields, level-aware aggregations, and evaluation order in Amazon QuickSight

Amazon QuickSight is a fast, cloud-native, serverless, business intelligence service that makes it easy to deliver insights to everyone. QuickSight has carefully designed concepts and features that enable analysis builders, such as QuickSight authors, to design content-rich, interactive, and dynamic dashboards to share with dashboard viewers. As authors build an analysis, QuickSight transforms, filters, and […]

Access Amazon Location Service from Amazon Redshift

Organizations typically store business and customer data in databases like Amazon Relational Database Service (Amazon RDS) and Amazon Redshift, and often want to enrich this data by integrating with external services. One such enrichment is to add spatial attributes such as location coordinates for an address. With the introduction of Amazon Location Service, you now […]

Synchronize and control your Amazon Redshift clusters maintenance windows

Amazon Redshift is a data warehouse that can expand to exabyte-scale. Today, tens of thousands of AWS customers (including NTT DOCOMO, Finra, and Johnson & Johnson) use Amazon Redshift to run mission-critical business intelligence dashboards, analyze real-time streaming data, and run predictive analytics jobs. Amazon Redshift powers analytical workloads for Fortune 500 companies, startups, and […]

Accelerate your data warehouse migration to Amazon Redshift – Part 2

This is the second post in a multi-part series. We’re excited to shared dozens of new features to automate your schema conversion; preserve your investment in existing scripts, reports, and applications; accelerate query performance; and potentially reduce your overall cost to migrate to Amazon Redshift. Check out all posts in this series: Accelerate your data […]

Establish private connectivity between Amazon QuickSight and Snowflake using AWS PrivateLink

Amazon QuickSight is a scalable, serverless, embeddable, machine learning-powered business intelligence (BI) service built for the cloud. QuickSight lets you easily create and publish interactive BI dashboards that include Machine Learning-powered insights. QuickSight dashboards can be accessed from any device, and seamlessly embedded into your applications, portals, and websites. QuickSight offers several sources for data, […]

Secure multi-tenant data ingestion pipelines with Amazon Kinesis Data Streams and Kinesis Data Analytics for Apache Flink

When designing multi-tenant streaming ingestion pipelines, there are myriad ways to design and build your streaming solution, each with its own set of trade-offs. The first decision you have to make is the strategy that determines how you choose to physically or logically separate one tenant’s data from another. Sharing compute and storage resources helps […]