amazon-quicksight

⛳️ PASS: Amazon Web Services Certified (AWS Certified) Data Analytics Specialty (DAS-C01) by learning based on our Questions & Answers (Q&A) Practice Tests Exams.

Self-hosted control plane for Amazon QuickSight that authors as well as administers: an assistant that plans dashboards and datasets with a wireframe before anything is written, a Studio that fixes what QuickSight refuses, account-wide playbooks, lineage, activity and the same API for people and agents. One CDK deploy into your own AWS account.

This project simulates a real-world enterprise data migration and modernization strategy. It extracts transactional data from a simulated "On-Premise" environment (hosted on AWS EC2), performs heavy distributed processing using a Hadoop/Spark cluster, and ultimately serves the data via a Cloud-Native, serverless architecture to optimize costs .

The Custom Connector Framework (CCF) is an open source AWS sample that simplifies building, running, and operating document ingestion from any document source into Amazon Bedrock knowledge bases, AWS Quick, or Amazon S3. You write the code that reads your source. CCF manages everything else a production connector needs.

Development of visibility forecast with elastic lead times using NWP model with DeepAR from past observation for the next 12/24 hours using DeepAR inside sagemaker studio and visualizing using AWS Quicksite with API service for clients for selected airports in the country.

In QuickSight, currently, one cannot transfer assets and delete user programmatically. This repository uses native QuickSight boto3 APIs to transfer all assets to a new owner and also delete the original owner.

With this self service reporting capability, QuickSight readers can now generate reports without elevating them to Authors.

Conversational analytics with Amazon Quick on an Amazon S3, AWS Glue and Amazon Athena lakehouse. AWS CDK (Python) deploys Q Topics and a custom chat agent over synthetic card-payments data with embedded patterns you can test against.

End-to-end AWS Business Intelligence reporting platform featuring data validation, Athena analytics, KPI governance, and executive dashboards.

This project lets users merge two analyses together and create a new analysis or even update the target analysis in place.

Tooling for migrating Qlik Sense dashboards into Amazon QuickSight modernizing legacy BI assets into a cloud-native analytics stack.

Python and AWS pipeline for portfolio optimization and tail-risk stress testing of four Tadawul stocks: 10,000-path Monte Carlo VaR/CVaR, Shapley risk decomposition, minimum-CVaR and cash alternatives, robustness checks and a VaR backtest, with a QuickSight dashboard and an Amazon Bedrock risk memo checked against the computed results.

Serverless ETL & Analytics Pipeline on AWS: Ingest, process, validate, query, visualize, and monitor financial data using Twelve Data API, S3, Glue, Athena, QuickSight, and CloudWatch.

This project about the police responses within Stockton, CA and how it impacts the decisions on whether someone wants to locate there or relocate based on how safe it is.

This sample demonstrates how to capture and enrich VPC Flow Logs, deduplicate observations with AWS Glue and Amazon Athena, identify cross-Availability Zone traffic by IP pair, estimate data transfer and Transit Gateway processing costs, and visualize the results in Amazon QuickSight.

E-commerce BI dashboard built with Amazon QuickSight for analyzing orders, revenue, fulfillment, and local & international sales.

Revenue Intelligence Dashboard in Amazon Quick — three siloed systems unified, three undocumented data defects found, and AI query accuracy measured before and after a semantic layer.

Análise estratégica de ROI e tendências de filmes, sustentada por um Data Lake serverless de ponta a ponta na AWS.

Revenue intelligence dashboard for a fictional B2B SaaS: three sources unified in Amazon Quick Suite, three interactive sheets, and a documented audit of where the AI answers failed. Udacity project, passed.