Category: Learning Levels

Amazon Redshift is a fully managed, petabyte-scale, massively parallel data warehouse that makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. We are continuously investing to make analytics easy with Redshift by simplifying SQL constructs and adding new operators. Now we are adding […]

Data lakes are a popular choice for today’s organizations to store their data around their business activities. As a best practice of a data lake design, data should be immutable once stored. But regulations such as the General Data Protection Regulation (GDPR) have created obligations for data operators who must be able to erase or […]

Data lakes provide a centralized repository that consolidates your data at scale and makes it available for different kinds of analytics. AWS Glue crawlers are a popular way to scan data in a data lake, classify it, extract schema information from it, and store the metadata automatically in the AWS Glue Data Catalog. AWS Lake […]

Amazon QuickSight Enterprise edition can integrate with your existing Microsoft Active Directory (AD), providing federated access using Security Assertion Markup Language (SAML) to dashboards. Using existing identities from Active Directory eliminates the need to create and manage separate user identities in AWS Identity Access Management (IAM). Federated users assume an IAM role when access is requested through an […]

Federated users of Amazon OpenSearch Service often need access to OpenSearch Dashboards with roles based on their user profiles. OpenSearch Service fine-grained access control maps authenticated users to OpenSearch Search roles and then evaluates permissions to determine how to handle the user’s actions. However, when an enterprise-wide identity provider (IdP) manages the users, the mapping […]

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. Data warehouses are mostly built using the dimensional model approach, which has consistently met business needs. Loading complex multi-point datasets into a […]

This post was co-written with Django Bouchez, Solution Engineer at Toucan. Business intelligence (BI) with dashboards, reports, and analytics remains one of the most popular use cases for data and analytics. It provides business analysts and managers with a visualization of the business’s past and current state, helping leaders make strategic decisions that dictate the […]

Amazon Redshift is the most widely used data warehouse in the cloud, best suited for analyzing exabytes of data and running complex analytical queries. Amazon QuickSight is a fast business analytics service to build visualizations, perform ad hoc analysis, and quickly get business insights from your data. QuickSight provides easy integration with Amazon Redshift, providing […]

Amazon EMR Serverless allows you to run open-source big data frameworks such as Apache Spark and Apache Hive without managing clusters and servers. With EMR Serverless, you can run analytics workloads at any scale with automatic scaling that resizes resources in seconds to meet changing data volumes and processing requirements. EMR Serverless automatically scales resources up […]

Organizations have chosen to build data lakes on top of Amazon Simple Storage Service (Amazon S3) for many years. A data lake is the most popular choice for organizations to store all their organizational data generated by different teams, across business domains, from all different formats, and even over history. According to a study, the […]