Category: Amazon Redshift

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.

Tens of thousands of customers use Amazon Redshift to process exabytes of data per day and power analytics workloads such as business intelligence, predictive analytics, and real-time streaming analytics. Learn how Etleap integrates with new data sharing and cross-database querying capabilities in Amazon Redshift to enable workload isolation for diverse analytics use cases in customer environments. Etleap integrates with any data source and runs either as a hosted solution (SaaS) or inside your VPC.

ThoughtSpot has developed a way for business people to easily answer their own data questions. Search-driven analytics is based on the concept that finding answers to business questions should be as easy as a basic internet search. With ThoughtSpot, there’s no need for SQL expertise or lengthy training sessions—rather, simple searches are translated into database queries and answers are calculated on-the-fly.

Built as a cloud-native service, Confluent Cloud offers developers a serverless experience with elastic scaling and pricing that charges only for what they stream. Confluent’s Kafka Connect Amazon Redshift Sink Connector exports Avro, JSON Schema, or Protobuf data from Apache Kafka topics to Amazon Redshift. The connector polls data from Kafka and writes this data to an Amazon Redshift database. Polling data is based on subscribed topics.

Google Analytics and Google Ads are popular platforms for customers who need to make data-driven decisions about the performance of their web assets. For prediction, testing, and optimization scenarios, however, customers need a broader and more complete set of analytics. Matillion is an ideal tool to combine the power and convenience of Amazon Redshift and Amazon QuickSight, providing cloud-native data integration tools that make loading and transforming data fast, easy, and affordable.

Fully managed cloud services enable global enterprises to focus on strategic differentiators versus maintaining infrastructure. They do this by creating data lakes and performing big data processing in the cloud. SnapLogic eXtreme allows citizen integrators, those who can’t code, and data integrators to efficiently support and augment data-integration use cases by performing complex transformations on large volumes of data. Learn how to set up SnapLogic eXtreme and use Amazon EMR to do Amazon Redshift ETL.

To help everyone visualize COVID-19 data confidently and responsibly, we brought together APN Partners Salesforce, Tableau, and MuleSoft to create a centralized repository of trusted data from open source COVID-19 data providers. Anyone can work with the public data, blend it with their own data, or subscribe to the source datasets directly through AWS Data Exchange, and then use Amazon Redshift together with Tableau to better understand the impact on their organization.

Mactores used a five-step approach to migrate, with zero downtime, a large manufacturing company from an Oracle on-premises data warehouse to Amazon Redshift. The result was lower total cost of ownership and triple the performance for dependent business processes and reports. The migration tripled the customer’s performance of reports, dashboards, and business processes, and lowered TCO by 30 percent. Data refresh rates dropped from 48 hours to three hours.