Course Outline
Introduction
- AWS QuickSight overview
- Definition of AWS and QuickSight
Initiating Use of AWS QuickSight
- Establishing AWS and QuickSight accounts
- Comprehending the QuickSight operational workflow
- Navigating the QuickSight user interface
Data Preparation in QuickSight
- Principles of data preparation within QuickSight
- Comparison between SPICE and direct query methodologies
- Methods for uploading and importing data to QuickSight
- Management of columns and fields
- Utilization of calculated fields, functions, and operators
- Incorporation of string-based calculated fields into projects
- Data extraction from string values
- Application of conditional functions
- Development of calculated fields utilizing numeric values
- Implementation of various filters within a project
Data Analysis and Visualization
- Distinguishing between data preparation and analysis processes
- Execution of data analysis tasks
- Generation of visual elements
- Conceptualization of dimensions and measures
- Inclusion of supplementary data sets
- Configuration of field formatting, aggregation, and granularity
- Styling of visual components
- Development of stories and treemaps
- Deployment of filters and tables
- Integration of Key Performance Indicator (KPI) visuals
Data Export and Sharing Protocols
- Mechanisms for refresh and scheduled updates
- Exportation of project data as .csv files
- Addition of users to an account for government access purposes
- Distribution of data sets and analyses
- Creation and dissemination of dashboards
Utilizing Databases as Data Sources
- Configuration of database environments
- Preparation of test data sets
- Establishment of QuickSight connections to databases
- Data importation into SPICE
- Data importation via direct query methods
- Incorporation of calculated fields and queries
- Leverage of NoSQL databases for government data needs
Summary and Next Steps
Requirements
- Foundational proficiency in analytical methodologies
Target Audience
- Professional data analysts
- Policymakers and stakeholders interested in data interpretation for government initiatives
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