Category: Amazon QuickSight

Business intelligence (BI) teams aim to automate Amazon QuickSight asset deployment across environments. CyberCX developed a solution using AWS Step Functions to orchestrate exporting QuickSight analyses from one environment and importing them to another, simplifying migration. This reusable module integrates with CyberCX’s broader serverless data platform but can standalone. The entire solution is designed with security in mind and follows the principles of least privilege access.

Amazon Q and generative BI are transforming business operations, and AWS Partners like ZS Associates, Tiger Analytics, and Compass UOL are pioneering use cases leveraging these technologies to build industry-tailored solutions that improve decision making, operations, fraud detection, software development lifecycles, and more. AWS provides resources to help partners develop and deploy such transformative generative AI offerings.

The world of video entertainment is more competitive than ever. The video entertainment landscape is crowded, so content providers must deeply understand viewer behavior to stand out. Synamedia Clarissa, built on AWS, delivers data-driven insights to help businesses boost viewer satisfaction. Clarissa analyzes video consumption and user experiences, providing content and app insights like which videos resonate best and how users discover content.

Many organizations want to migrate from legacy BI tools to Amazon QuickSight, but manual migration cab be costly. Wavicle’s QuickSight Migration Solution (QMS) automates and optimizes this process, analyzing existing dashboards, identifying duplication, automating conversion, and facilitating a seamless rollout. This reduces migration effort, costs, and risks so organizations can rapidly realize QuickSight’s self-service analytics, flexibility, and cost savings.

A content delivery network (CDN) caches content closer to users and reduces load times. Monitoring CDN performance is crucial for optimizing user experience, and this post demonstrates building an Amazon QuickSight dashboard with generative AI capabilities to gain insights from Fastly CDN logs in Amazon S3. It covers configuring real-time log streaming, using AWS Glue to catalog data, accelerating dashboard creation using natural language, and creating rich data stories for stakeholders.

Many AWS customers using SQL Server for analytics seek to migrate to Amazon QuickSight, a cloud-native business intelligence that provides interactive dashboards and charts unmatched by SQL Server Reporting Services (SSRS). IPsense developed a tool to accelerate migrating SSRS reports to QuickSight which automates converting SSRS queries and stored procedures into AWS Glue jobs that populate a cloud data lake.

Online analytical processing (OLAP) is a method of organizing datasets in a multi-dimensional format for quick analysis and provides deeper insights for decision-makers. Multi-dimension analysis is widely adopted by analysts, knowledge users, and power users for their decision support process. Learn how utilizing AWS analytic services and migration tools together with HCLTech frameworks to orchestrate OLAP solutions.

Modern enterprise customers use AWS Marketplace datasets along with their business and operational data to create meaningful and deeper insights to improve their customer experience. Learn how to consume datasets from AWS Data Exchange to transform and store data in Databricks Lakehouse Platform using Delta Live Tables (DLT) and visualize it in Amazon QuickSight. DLT is a framework for building reliable, maintainable, and testable data processing pipelines.

Amazon QuickSight is an easy-to-use, cloud-powered analytics business intelligence tool that provides insights and analytics capabilities. Experts from AWS and Quantiphi, an AWS Premier Tier Services Partner, discuss an approach to assist users in leveraging Amazon QuickSight as an enterprise-wide BI tool. The entire process, creation of data sources, datasets, analysis, and eventually dashboards, can be automated using AWS CodePipeline.

Many organizations record calls which are potential gold mines of rich insights about customer satisfaction, customer churn, competitive intelligence, service issues, agent performance, and campaign effectiveness. However, the sheer volume of phone calls exceeds a contact center’s ability to review and analyze them in order to glean those valuable insights. Learn how SourceFuse used custom microservices development to design a call center solution for a healthcare customer.