Category: Amazon Redshift

IT teams are always exploring solutions to increase their existing investments and looking for solutions that answer business needs in line with IT objectives. Learn the benefits of adopting a composable customer data platform (CDP), discover ActionIQ’s Customer Experience (CX) Hub, and understand how ActionIQ and Amazon Redshift enable a composable CDP. This helps technical teams extend and enhance existing technology investments to manage data governance, costs and performance.

To reduce the technical complexity and manual processes needed to build pipelines that meet various security policies, Fivetran offers flexible connection options to securely and reliably move enterprise data from source to destination. Fivetran runs on AWS and can support customers syncing data from databases and to destinations hosted on AWS, including the Amazon Redshift data warehouse. Integration with AWS PrivateLink also allows customers to send data without using the public internet.

Setting and monitoring clear, appropriate, and actionable reliability goals can be a challenging task, especially in large-scale businesses. Nobl9 helps organizations use service-level objectives (SLOs) to find a balance between operational efficiency, reliable delivery of services, cost control, and customer satisfaction. Explore how you can use Nobl9’s integration with Amazon Redshift to easily set up SLOs on top of your product data and derive actionable insights.

AWS partners have asked us to do more to help them build analytics-driven applications, so we are excited to announce the launch of the ‘Powered by Amazon Redshift’ program. This program enables ISVs to build their applications using Amazon Redshift—our fully-managed cloud data warehouse service—and deliver fast, easy, and secure analytics at any scale available within their applications. With Amazon Redshift powering applications, ISVs can drive up to 3X price performance compared to any other cloud data warehouse.

One of the biggest advantages of VMware Cloud on AWS is that it can readily integrate with other AWS services. That gives you countless ways to elevate your workloads. If you’re amassing data in your databases over time and are looking for novel ways to glean fresh insights out of it, using Amazon Redshift and Amazon QuickSight is an easy and accessible way to achieve it. This post describes how to get more out of existing data residing inside your databases running in VMware Cloud on AWS.

More people are using data today than ever before, but it’s getting harder and harder for everyone to collaborate on the same data. Atlan has pioneered a collaborative workspace helping modern data teams work together better. Atlan is a collaboration and orchestration layer—the glue that brings together your team, the tools you love, and the data you need. Learn how companies use Atlan and AWS to democratize their data, collaborate more effectively, and unify knowledge and context in one place.

Although the business case for digital analytics is well-articulated, many organizations are looking for ways to build stronger cases around transformations by consolidating data generated across the enterprise with customer behavioral data. Learn how Softcrylic developed the Analytics Shift solution which helps businesses bring Adobe Analytics data into Amazon Redshift to drive deeper insights and data integration.

Spatial data is a vital ingredient in today’s applications, enabling capabilities ranging from asset tracking and location-based marketing to monitoring deforestation and more. Learn about the most important areas that organizations need when working with spatial data in Amazon Redshift and how CARTO helps them unleash unique spatial visualization, analysis, and app development features right inside AWS’s cloud data warehouse.

In early August, millions of people took part in the 2021 Census across Australia, providing a comprehensive picture of the country’s economic, social, and cultural makeup. The Australian Bureau of Statistics (ABS) ran the 2021 Census on AWS using an operational insights platform built in partnership with AWS Professional Services, Shine Solutions, ARQ Group, and the ABS. Learn how this tool provided near real-time insights into a very complex logistical activity.

Building effective machine learning models requires storing and managing historical data, but conventional databases can quickly become a nightmare to regulate. Queries start taking too long, for example, slowing down business decisions. Learn how to use Amazon Redshift ML and Query Editor V2 to create, train, and apply ML models to predict diabetes cases for a sample diabetes dataset. You can follow a similar approach to address other use cases such as customer churn prediction and fraud detection.