This demo shows building a self-serve QuickSight dashboard for a sales VP to review last week's performance, reducing back-and-forth with analytics and enabling questions beyond the dashboard.

Learn to create drill down in a report by adding product name under category, then apply region and order status filters to update charts across the sheet.

Explore how QuickSight scenarios use generative ai for what-if modeling with natural language to analyze revenue impact, customer segments, and price-change scenarios across dashboards.

Explore quick chat spaces and external connections in QuickSuite, and watch a demo that contrasts default versus custom agents, shows organizing spaces, data sources, attachments, and 24/7 availability.

spaces in quicksuite act as a knowledge center for a team, aggregating data and files; attach return policy and warranty guide, then query the space-bound agent for precise answers.

Demonstrate creating a web crawler, configuring knowledge bases and actions, and integrating Jira with Asana and Confluence using REST, open APIs, and API tokens.

Explore a demo use case where SomeCompany Ventures analyzes AIML investment opportunities, using the Amazon Quick Research service to assess market size, growth, competition, risk, and recommendations.

Build a customer support flow in QuickSuite that takes customer email and order number, retrieves order details, checks shipping status, and generates customer and internal emails plus a summary.

Create a new Slack workspace and configure the Quick Suite connector with base URL, client ID, client secret, and redirect URL, then sign in and test the channel post.

Configure and test quick flows to post a Slack summary for competitive intelligence, exploring Dell and HP trends, product launches, pricing, and leadership changes via a multi-step research flow.

Demonstrates building an automation to list S3 invoices, extract file names from contents, and write data into an Excel workbook for downstream processing, with logging and debugging steps.

Demonstrates creating an excel workbook, writing textract-derived unpaid invoice data to sheet 'invoice', saving as xlsx, uploading to S3, and debugging vendor versus customer fields and folder processing.

Build a loop to move processed invoices by copying them to the processed invoices folder and deleting the originals, preventing reprocessing and enabling automated invoice tracking in an Excel sheet.

Rename the automation to invoice processing, commit and deploy changes, schedule a daily trigger at 10 p.m. Eastern Time using cron expressions, and deactivate triggers during testing to control costs.