Category: Amazon Redshift

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.

There has been a lot of buzz about a new data architecture design pattern called a Lake House. A Lake House approach integrates a data lake with the data warehouse and all of the purpose-built stores so customers no longer have to take a one-size-fits-all approach and are able to select the storage that best suits their needs. Learn how to couple Amazon Redshift with a semantic layer from AtScale to deliver fast, agile, and analysis-ready data to business analysts and data scientists.

Data warehouse modernization has been a key aspect of many customers’ broader cloud transformation stories. Legacy data warehouse systems, however, present many challenges when dealing with today’s enterprise data needs. Learn how AWS and Infosys collaborated to transform a legacy Netezza platform on AWS for a large retail customer. With Infosys tools, processes, and industry knowledge, the collaboration between AWS and Infosys enables customers to transform their analytics platforms.

With increasing data variety and volumes, it’s become increasingly necessary to ensure all of an organization’s workloads run in the most efficient manner to reduce overall turn-around time and TCO. Get an overview of the data and analytics platform ZS built to streamline and improve contracting analytics for a top life sciences company. Then, dive deep into the data architecture and learn how ZS evolved its data technology stack to get maximum performance.

Many companies are using Amazon Redshift to analyze and transform their data. As data continues to grow and become even more important, they are looking for more ways to extract valuable insights. One use case we’re especially excited to support is that of data tokenization and masking. Amazon Redshift has collaborated with Protegrity, an AWS Advanced Technology Partner, to enable organizations with strict security requirements to protect their data while being able to obtain the powerful insights.