General Performance Key Driver Analyses (KDAs) are perhaps the most common type of analysis you can run in Sisu, and are useful for providing an overall “birds-eye view” of your organization’s data and its implications.
 |
Since data analysis is iterative in nature, you can edit and re-run your Analysis configuration at any time. Alternatively, you can copy the Analysis and edit copy instead, to leave your original Analysis configuration intact. Refer to Duplicating and Editing an Analysis |
Related Articles:
- Understanding Key Driver Analyses
- Interpreting a General Performance Analysis
- Tuning an Analyses with Advanced Settings
What is a General Performance KDA?
A General Performance KDA is one of the three analysis types that Sisu performs:
- General Performance
- Time Comparison
- Group Comparison
This type of analysis provides an “overall” analysis of your data. Sisu explores all possible combinations of data points in your data, determines the relevant statistics for each subgroup, and then uses our algorithm to determine which subgroups are statistically significant.
|
Statistical significance is driven by the potential impact the information from the data combination will have on possible outcomes in your business. |
For more details, please refer to Understanding Key Driver Analyses.
.
Configuring a General Performance KDA
To create and configure a General Performance KDA:
- Ensure that you have either uploaded data to Sisu or have connected to a data source.
Refer to the “Connecting to External Data Sources” articles in the Data Input & Connections section for details on connecting to a data source.
- From the Projects module, select the Project Name you wish to work with.
- Select a Metric for your analysis.
Refer to Defining a Metric for details. - Click + to to display the “Create new analysis”modal. Select Key Driver Analysis, type a descriptive name, and click Create analysis.
General Performance is the default analysis type when creating a new Analysis. The Analysis uses the calculation type defined in the Metric selected in Step 3.
The analysis automatically includes all data columns within the dataset. However, if you need to remove any data point, you can use the Manage columns button to deselect them. Refer to Managing Columns for an Analysis - Select Custom filter to define any filters you would like to apply to the Analysis.
Refer to Setting Custom Filters for more information. - Optional: Click hoose any additional settings you would like for your Analysis.
Refer to Understanding Sisu's Statistical Models for more information on available advanced settings. - Click "Run".
Sisu will process the Analysis and display the results.
If you receive a “Run failed” message, you can click “Show details” to display information about what went wrong. Usually, it’s a problem with the data that can be easily fixed.
Refer to Troubleshooting Common Issues for further assistance.
NEXT STEP:
Refer to Interpreting a General Performance Analysis for information on understanding the analysis results.