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 Duration 14 hours

Course Outline

Course Introduction

  • Foundational overview of AWS QuickSight capabilities
  • Definition and role of AWS and QuickSight within cloud infrastructure

Initial Configuration and Setup for government

  • Provisioning of AWS and QuickSight user accounts
  • Comprehensive understanding of the QuickSight operational workflow
  • Interface navigation and UI familiarization

Data Preparation Methodologies in QuickSight

  • Foundational principles of data preparation processes
  • Comparative analysis of SPICE in-memory vs. direct query modes
  • Procedures for uploading and importing external data assets
  • Management of data columns and logical fields
  • Mastery of calculated fields, functions, and logical operators
  • Implementation of string-based calculated fields in analytical projects
  • Techniques for extracting relevant information from string data types
  • Application of conditional logic and functions
  • Generation of calculated fields utilizing numeric data
  • Strategic application of filters within project scopes

Data Analysis and Visualization Protocols

  • Distinction between data preparation and analytical execution phases
  • Construction of data analysis frameworks
  • Development of visual representations of data
  • Conceptual understanding of dimensions and measures
  • Integration of supplementary data sets
  • Optimization of field formatting, aggregation methods, and granularity levels
  • Standardization of visual output formatting
  • Creation of narrative stories and treemap visualizations
  • Utilization of advanced filters and tabular views
  • Incorporation of Key Performance Indicator (KPI) visuals

Data Export and Collaborative Sharing for government

  • Management of data refresh schedules and automated updates
  • Exporting project data in CSV format
  • User account management and access provisioning
  • Secure sharing of data sets and analytical models
  • Deployment and distribution of dashboards

Integration of Database Systems as Data Sources

  • Configuration and setup of database environments
  • Preparation of test or dummy data sets
  • Establishing secure connections between QuickSight and databases
  • Importing data into the SPICE engine
  • Importing data via direct query methods
  • Integration of calculated fields and complex queries
  • Interaction with NoSQL database architectures

Concluding Summary and Recommended Pathways

Requirements

  • Foundational knowledge and comprehension of data analysis principles

Intended Audience

  • Professional data analysts
  • Personnel with a professional interest in data analysis and visualization for government

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