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The steps in this article are for Dashboards & Analytics (Amazon Q) users only. If you use Reports (Microstrategy), proceed to these articles instead.
This article covers the following:
- Understanding Datasets
- Combining Datasets Using Joins
- Building an Analysis from a Combined Dataset
- Applying Office-Level Security Filters
Understanding Datasets
Datasets are the data foundation for analyses and dashboards. A dataset contains the fields available to build visuals, filters, and calculations.
Key terms
- Field: A single data element or column.
- Dimension: A descriptive field used for grouping or labeling.
- Measure: A numeric field used for totals, counts, averages, and comparisons.
Before building complex reporting, review the available dataset fields and confirm they support the business questions you want to answer.
For a full list of the dataset fields, review the Data Dictionary. The spreadsheet also includes the object equivalent for clients that are migrating from Microstrategy.
Combining Datasets Using Joins
You can combine datasets to bring related records together for analysis. This is useful when the data you need is spread across more than one source dataset.
See this video for more information on combining datasets.
- Open a dataset.
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Select Use in Dataset under the Use in Analysis dropdown.
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Click Add Data.
- Choose Dataset from the dropdown.
- Select the second dataset.
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Click Select.
- Click the join clause using the connector between the datasets.
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Select the fields from each dataset from the dropdown. Click Add a new join clause to select additional fields.
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Select the join type.
Join Type Description When to Use It Inner Join Includes only rows that have matching values in both datasets. Records that don’t exist in both are excluded Use this when you want to analyze data that exists in both datasets. For example, only matters that also have invoices. Left Join Includes all rows from the left (primary) dataset and only the matching rows from the right dataset. Rows from the left dataset with no match in the right will still appear, but right-side fields will be blank. Use this when you want all records from the left dataset, even if there’s no corresponding data on the right. For example, all matters, even if some have no invoices. Right Join Includes all rows from the right (secondary) dataset and only the matching rows from the left dataset. Rows from the right dataset with no match on the left will still appear but left-side fields will be blank. Use this when you want all records from the right dataset, even if there’s no match on the left. For example, all invoices, even if some are not linked to a matter. Full Join Includes all rows from both datasets. When there’s no match, fields from the opposite dataset will remain blank. Use this when you need a complete view of all records from both datasets. For example, to identify unmatched matters or invoices. - Click Apply.
- Review the preview results.
- Click Save & Publish.
If your results look incomplete or unexpectedly large, test the effect of changing the join type and preview the dataset again before saving.
Building an Analysis from a Combined Dataset
After combining datasets, you can build an analysis to validate the data model and create a dashboard that uses the joined data.
- Click Analyses from the left navigation panel.
- Click New Analysis.
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Select the combined dataset. You can view combined datasets by the link icon on the set.
- Click Use in Analysis.
- Select the sheet type.
- Add visuals using fields from the joined dataset.
- Add filters and controls.
- Publish the dashboard.
- Review the dashboard to validate that the data behaves as expected.
Review and validate the published dashboard. If you need to make changes, open the analysis, make your changes, and choose the Replace existing dashboard option.
Applying Office-Level Security Filters
Data security filters limit which records appear in a dashboard. A common use case is restricting data by office or department.
See this video on applying office-level security filters and more.
- Open the analysis.
- Locate the appropriate office-related field in the dataset. For example, these may be Contact Office or Office Name.
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Click Filters in the top tool bar.
- Optional: Click Add to add the field as a filter if it is not already present.
- Click the vertical ellipses next to the filter.
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Select Edit.
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Select Cross-sheet to apply the filter to all sheets.
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Specify the office(s) to allow access. Review the visuals on each sheet to ensure accuracy.
- Click Publish.
Always validate published security-filtered dashboards after publishing to confirm they only display authorized data.