Category: Intermediate (200)

Amazon QuickSight is an IAM Identity Center enabled application. Administrators can create a new QuickSight account and use IAM Identity Center for managing QuickSight users and groups. IAM Identity Center can store QuickSight user and group identities within IAM Identity Center itself as an identity store, or they can configure it with a third-party identity provider (IdP) used within their organization. Administrators can use groups in their IdP to assign QuickSight roles (administrator, author, and reader) to users. After they’re successfully authenticated via IdP, users can seamlessly access QuickSight dashboards either from the QuickSight application or as an embedded component within their business applications. Having QuickSight users and groups provisioned in an IdP also helps control authorization to QuickSight resources like dashboards and datasets.In this post, we discuss when you should use which type of instance, the benefits of using IAM Identity Center with QuickSight, how to configure an account instance, and how to use it to access QuickSight.

This post delves into integrating QuickSight with Slack through AWS Chatbot. AWS Chatbot serves as a ChatOps tool within AWS, facilitating communication and commands through chat clients. It supports notifications from AWS services to chat channels, streamlining monitoring and issue resolution processes.

Amazon QuickSight supports identity federation through Security Assertion Markup Language 2.0 (SAML 2.0) in both Standard and Enterprise editions. With federation, you can manage users using your enterprise identity provider (IdP) and pass them to QuickSight at login. IdPs include Microsoft Active Directory Federation Services, Ping One Federation Server, Okta, and more. This post provides steps and code samples to overcome these challenges in a scalable way. We demonstrate the solution using Okta, but you could use other IdPs as well. This is a proven solution and has been used and implemented by several QuickSight customers.

Prevsis aims at caring for workers’ safety, well-being, and corporate sustainability. It focuses on delivering a no-code occupational health and safety (HS) and environmental, social, and governance (ESG) solution with a wide range of data pipelines for robust analytics harvesting with AI capabilities. Users in high-risk industries such as mining, energy, construction, and logistics can digitally manage all their safety and compliance needs through a one-stop interface. As one of the leading digital service providers in the HS/ESG field Latin America, we capitalize on decades of experience to help customers assess and monitor risk levels, enhance operational efficiency, and minimize disruptions across the workplace. In this post, we share how Prevsis used Amazon QuickSight to create more than 700 client dashboards.

Global Mile is a foundational team within Amazon that helps to build, manage, and operate its global transportation network for orders that cross international borders. Global Mile Exports Visibility was set up in 2019 to architect and own the team’s data management, strategy, and underlying platform. In this post, we discuss how Global Mile migrated their BI dashboards and reports to Amazon QuickSight to enhance their operations.

Amazon QuickSight is a fully managed, cloud-native business intelligence (BI) service that you can use to connect to your data and create interactive dashboards that can be shared with tens of thousands of users. The dashboards can be used within QuickSight or embedded in software as a service (SaaS) apps. As we bid farewell to […]

Amazon QuickSight is a cloud-native, serverless business intelligence (BI) service that lets you build visualizations, perform ad hoc analysis, and gain insights through machine learning (ML) capabilities such as anomaly detection, forecasting, and natural language querying. QuickSight utilizes its robust in-memory engine SPICE (Super-fast, Parallel, In-memory Calculation Engine) to rapidly perform advanced calculations and deliver visuals.BigQuery is Google Cloud’s fully managed, petabyte-scale, cost-effective analytics data warehouse that lets you run analytics over vast amounts of data in near-real time. In this post, we walk you through the permissions and connection details needed in BigQuery to bring BigQuery data into QuickSight through OAuth and create a simple dashboard.

Recently, we launched a range of new features for Tables and Pivot Tables in QuickSight centered around interactivity and performance, allowing you to alter field visibility, load tables faster, and build consistency across different interactions. Building on this momentum, we are excited to unveil two additional capabilities, this time with a focus on improving readability, presentation, and space optimization.

This post helps cloud architects, cloud engineers, and developers build embedded analytics architectures on the AWS Cloud using AWS purpose-built data analytics services and Amazon QuickSight by providing various architectural patterns for building personalized dashboards based on user role or job function. We also discuss best practices and key considerations that showcase the power of embedded analytics, and share additional resources for getting started with building embedded analytics on AWS.

Are you finding it cumbersome to scroll horizontally in pivot tables to see all your row fields? Are you dealing with data that has a hierarchical structure, like cost center or product hierarchies? If you are, then there’s exciting news for you! Amazon QuickSight now offers a new layout option called hierarchy layout for pivot […]