Quick Suite
Best Practice

Effective Use of Filters and Parameters: Consider how filters will interact with visuals. Use Quick Suite Controls and Parameters to manage the flow of filter conditions, ensuring that users can quickly focus on the data that matters most without unnecessary overhead.
Cascading filters affect will not be possible in case of separate dataset strategy when used for performance enhancement of filters.
Cascading filters affect works as expected in case of SPICE Datasets when all the filters are derived from same dataset.

Leverage Aggregated Datasets for Performance: Build aggregated datasets from your most granular (atomic) datasets to improve dashboard performance. Ensuring that attribute (column) names remain consistent between aggregated and atomic datasets makes it possible to implement drill-down features from summary to detail views.
Avoid Complex Joins in Quick Suite: Pre-join or prepare data before importing into SPICE, especially when using AWS Athena on large datasets. Quick Suite does not support joining multiple datasets on the fly, but it does allow drilling down from aggregated datasets to underlying atomic datasets if attributes and naming conventions are consistent.
Dimensions with many unique values should be used as a separate SPICE dataset to improve the performance when used as a filter
Develop KPI cards using aggregated dataset used for filters creation. This will help develop filters and apply across datasets.

Optimize SPICE Usage: To achieve optimal performance, load pre-aggregated, well-prepared data into SPICE. Store a replica in your source data system to ensure that SPICE refreshes are quick and reliable.
Simplify SPICE Refresh Queries: Keep SPICE refresh queries as straightforward as possible—simple SELECT * statements from already prepped, clean datasets. Perform all necessary transformations, aggregations, and joins before loading data into SPICE to reduce refresh failures and improve scalability.
Plan for Large Datasets: If certain atomic datasets are too large or wide to fit into SPICE, use Direct Query. Ensure that these source datasets are properly partitioned and indexed, and test response times for various filter conditions before pointing Quick Suite to them. Quick and reliable queries at the source layer will translate into faster, more responsive dashboards.

Governance & Access Control: Implement data governance policies to maintain accuracy, efficiency, and security. Use a combination of datasets, data sources, and shared analyses to manage and control data access and enhance data quality.
Minimize On-the-Fly Transformations: Perform complex transformations, filtering, and aggregations in the ETL pipeline or at the source database. Limit the use of Quick Suite calculated fields to essential scenarios to avoid performance bottlenecks and complexity.

Controlled Model Changes: When updating datasets or SPICE imports, test all dependent analyses and dashboards thoroughly. Use dataset versioning to manage updates and ensure a controlled, predictable transition when deploying changes.

Strategic Direct Queries: For large atomic datasets unsuited for SPICE, use Direct Query mode. Before enabling drill-down to these datasets, ensure the source can handle multiple columns and complex filters efficiently. Test response times and indexing strategies (e.g., partitioning, sorting, indexing) to ensure that Quick Suite visualizations remain performant and responsive.

Dynamic Environment Parameters: Use Quick Suite Parameters for database and table names to streamline deployment across development, test, and production environments. This ensures simpler maintenance and less manual reconfiguration.

Right Visualization for the Task: Experiment with Quick Suite’s diverse range of charts, tables and maps (including Amazon Quick Suite Q) to match the nature of your data and the needs of your audience.
Utilize KPI Widgets: Use KPIs or Key Metric Widgets to highlight critical numbers and track key metrics. Clear and prominent KPI visuals guide users’ attention and help them quickly interpret the health and trends within the data.

Create user groups that align with specific roles (e.g., Analyst, Developer, Admin) or business units (e.g., Sales, Marketing, Finance).Avoid creating too many overlapping or redundant groups, as this can complicate permissions management.
Integrate Amazon Quick Suite with AWS IAM (Identity and Access Management) for centralized user management and consistent permissions
Use Quick Suite audit logs to identify any unauthorized access or anomalies.
Use clear and consistent naming conventions for groups to make it easy to understand their purpose (e.g., QS-Admins, QS-Analysts-Marketing).

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