Category: *Post Types

In this post, we explore how to create a simple serverless architecture using AWS Lambda, Amazon Athena, and QuickSight to establish column level lineage. Tracking column-level lineage provides a clear view of each column’s path through different parts of QuickSight, helping to optimize data processing, improve query performance, ensure accuracy, and meet regulatory requirements.

Wake, a leading ecommerce platform provider, transformed its business intelligence capabilities by migrating to Amazon QuickSight. In this post, learn about how QuickSight enables Wake to make more informed, agile, and cost-effective decisions.

In this post, we’ll share how Mindex, a leading provider of enterprise software development and cloud services, partnered with QuickSight to enhance speed and experience and offer advanced analytics to more than 410 school districts through the SchoolTool Platform. We’ll explore how Mindex used QuickSight to build efficient dashboards and used Amazon Q in QuickSight, harnessing the power of generative artificial intelligence (AI) to make dashboard developers more efficient.

Amazon Logistics (AMZL) is the Amazon last-mile delivery network. The goal of AMZL is to provide customers with a seamless package delivery service across multiple geographies. AMZL plays a critical role in Amazon Transportation’s supply chain by using continuous improvement initiatives and creative thinking to ensure that millions of packages reach their destination as efficiently as possible. Amazon QuickSight reporting and BI infrastructure hosts more than 3,200 dashboards that are consumed by over 30,000 users across the company with average weekly active users of more than 17,500. Critical insights such as AMZL daily and weekly business reviews, operational metrics that help visualize corporate business outcomes and drivers, and operational insights for delivery station managers and AMZL leadership are all hosted in Amazon QuickSight, making it the one-stop shop for AMZL analytics and reporting. In this blog post, we share the challenges AMZL faced with their previous BI solution, their migration to QuickSight, and the best practices that helped the AMZL team to reduce costs and improve performance to help stakeholders make data-driven decisions.

With over 5350 branches, 8 international offices, and over 16,000 ATMs, Axis Bank is India’s third-largest private sector bank. In this post, we share how Axis Bank used Amazon QuickSight to achieve highly scalable modern business intelligence (BI). As part of our digital transformation journey, we started using AWS to modernize our applications to be cloud-centered. We’ve deployed several mission-critical applications on AWS, from onboarding journeys for Savings, Salary, Staff Account, central Know Your Customer (KYC) platform for video KYC, eKYC, to credit card servicing application.

Pixel-perfect reports in Amazon QuickSight enable you to create and share highly formatted, personalized reports containing business-critical data to hundreds of thousands of end-users without infrastructure setup or maintenance, upfront licensing, or long-term commitments. To save time copying the same visual multiple times to filter for different values and generate an invoice for all your customers, you can use repeating sections in pixel-perfect reports. With repeating sections, authors can build visuals in a report one time but have the system repeat for as many values of a dimension exist. In this post, we demonstrate how to use this new feature.

Prospect is a data analytics company helping the sports industry use artificial intelligence (AI) to power decisions—from the field to the boardroom. Our customers include teams, leagues, governing bodies, broadcasters, ticketing agencies, and sponsors. In this post, we share how we partnered with Amazon QuickSight to shift our business model from a mainly consultative approach to offering our powerful data analysis and business intelligence (BI) tools directly to customers.

In this post, we discuss how CloudSmart partnered with Amazon QuickSight to enhance the speed, experience, and data depth of its offering for one of its major customers, RISCPoint, a cybersecurity and compliance specialist.

This blog post shows how data owners and business intelligence (BI) administrators can centrally manage fine-grained data permissions on Amazon Redshift tables and views and enforce them on all users in Amazon QuickSight with AWS IAM Identity Center trusted identity propagation.

Amazon QuickSight is a cloud-powered, serverless, and embeddable business intelligence (BI) service that makes it straightforward to deliver insights to everyone in your organization. As a fully managed service, QuickSight lets you create and publish interactive dashboards that can then be accessed from any device and embedded into your applications, portals, and websites. QuickSight is expanding filter and control functionality. Previously, a filter could be scoped to a single visual, some visuals, all of the visuals for a dataset on a sheet, or all applicable visuals on a sheet. With the launch of cross-sheet filters and controls, authors can now create, delete, and edit filters that apply to multiple sheets. Previously, cross-sheet filters could be created with parameters in over forty clicks. With the expansion in functionality, they can be created in just five clicks, which shows how much this new feature simplifies setting up filters and controls that impact multiple sheets.