Category: Learning Levels

AWS Lake Formation makes it easier to centrally govern, secure, and share data for analytics with familiar database-style grant features managed through the Glue Data Catalog. Lake Formation provides a single place to define fine-grained access control on catalog resources. These permissions are granted to the principals by a data lake admin, and integrated engines […]

Amazon Redshift is a fully managed, petabyte scale cloud data warehouse that enables you to analyze large datasets using standard SQL. Data warehouse workloads are increasingly being used with business-critical analytics applications that require the highest levels of availability and resiliency. Amazon Redshift is a cloud-based data warehouse that already supports many recovery capabilities to […]

Amazon DynamoDB is ideal for applications that need a flexible NoSQL database with low read and write latencies and the ability to scale storage and throughput up or down as needed without code changes or downtime. You can use DynamoDB for use cases including mobile apps, gaming, digital ad serving, live voting, audience interaction for live […]

Amazon Redshift is a fast, petabyte-scale cloud data warehouse delivering the best price–performance. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Today, tens of thousands of customers run business-critical workloads on Amazon Redshift. Dynamic data masking (DDM) support in Amazon Redshift […]

Amazon Redshift is a fast, petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all of your data using standard SQL and your existing business intelligence (BI) tools. Tens of thousands of customers today rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, delivering the best price-performance. […]

This is a guest post by AWS Data Hero and co-founder of Conduktor, Stephane Maarek. Deploying Apache Kafka on AWS is now easier, thanks to Amazon Managed Streaming for Apache Kafka (Amazon MSK). In a few clicks, it provides you with a production-ready Kafka cluster on which you can run your applications and create data […]

Amazon EMR provides a managed service to easily run analytics applications using open-source frameworks such as Apache Spark, Hive, Presto, Trino, HBase, and Flink. The Amazon EMR runtime for Spark and Presto includes optimizations that provide over two times performance improvements over open-source Apache Spark and Presto, so that your applications run faster and at […]

Organizations are working towards centralizing their identity and access strategy across all their applications, including on-premises, third-party, and applications on AWS. Many organizations use identity providers (IdPs) based on OIDC or SAML-based protocols like Microsoft Azure Active Directory (Azure AD) and manage user authentication along with authorization centrally. This authorizes users to access Amazon QuickSight […]

In this post, we show how to use Amazon QuickSight and Amazon Athena Federated Query to build dashboards and visualizations on data that is stored in Microsoft Azure Synapse databases. Organizations today use data stores that are best suited for the applications they build. Additionally, they may also continue to use some of their legacy […]

Amazon Athena now enables data analysts and data engineers to enjoy the easy-to-use, interactive, serverless experience of Athena with Apache Spark in addition to SQL. You can now use the expressive power of Python and build interactive Apache Spark applications using a simplified notebook experience on the Athena console or through Athena APIs. For interactive […]