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
Testimonials (3)
Deepthi was super attuned to my needs, she could tell when to add layers of complexity and when to hold back and take a more structured approach. Deepthi truly worked at my pace and ensured I was able to use the new functions /tools myself by first showing then letting me recreate the items myself which really helped embed the training. I could not be happier with the results of this training and with the level of expertise of Deepthi!
Deepthi - Invest Northern Ireland
Course - IBM Cognos Analytics
he was well prepared - and he is very sympathetic
Oliver - Post CH AG
Course - Splunk Fundamentals
lots of pratical exercises