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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 glossary defines the key data and dashboard concepts used throughout the Dashboards and Analytics tool.
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Reader License
- Dashboard: An interactive, read-only data visualization report with features that allow you to filter, export, and drill down into details to gain business intelligence.
- Shared Folder: A company-designated area where dashboards can be accessed by those with permission.
- Control: An on-screen element (dropdown, slider, text box) linked to a parameter.
- Parameter: A dynamic input variable that allows you to filter data displayed on dashboards.
- Sheet: A page, or tab, within a dashboard with visuals or text boxes.
- Bookmark: A saved dashboard view with specific filters and parameters applied.
- Q&A: An optional feature that, if enabled, allows you to type questions in everyday or natural language and receive answers, like “What was the approved matter spend by law firm in 2025.”
Author License
Publishing & Collaboration
- Publish: Converts an analysis into a dashboard viewable by others.
- Dashboard: The published, read-only version of an analysis for shared viewing.
- Version History: Tracks all versions of a dashboard for easy restoration.
- Share: Grant access to published dashboards, analyses, or datasets. Sharing ensures that only approved users or groups can view or edit content, supporting both collaboration and data security.
- Shared Folder: A company-designated area where dashboards and datasets can be accessed by those with permission.
Data Foundations
- Data Source: The original system that provides data (e.g., CounselLink).
- Dataset: A prepared collection of data fields used for analyses and dashboards.
- Field: A single column or data element within a dataset. Each field holds a specific type of information — for example, Matter Name, Invoice Amount, or Contact Office. Fields can be text, numbers, or dates.
- Dimension: A descriptive or categorical field, typically text or date based. Used to group, filter, or label data (e.g., Office, Matter Name, or Invoice Date) and to provide context for numeric measures. They appear with blue icons in the field list.
- Measure: A numeric field used for calculations, comparisons, and aggregations (e.g., Billed Amount, Matter Count). Measures support totals, averages, and trend calculations. They appear with orange icons in the field list.
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Join: A method of combining multiple datasets based on a join clause.
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Join Types (e.g., Inner, Left, Right, and Full) determine which records are included in the combined dataset.
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. -
Join Clauses define define the unique field(s) used to link datasets. The table below lists several examples.
Main Dataset Join Clause (Field) Can Join to These Datasets MatterData CounselLinkTrackingID MatterJournal
MatterBudget
MatterAccrual
MatterAllocation
MatterReserveChange
InvoiceData Invoice Charge
InvoiceData CounselLinkInvoiceID Invoice Charge
Charge Adjustment Data
Invoice_skey Invoice Event
InvoiceAllocationData
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Analysis Workspace
- Analysis: A workspace for exploring and building visuals before publishing.
- Visual: A chart, KPI, or table that presents data from a dataset.
- Insights: Automatically generated visuals or narratives that highlight data trends.
- Properties: Formatting panel for visuals and sheets, controlling titles, layout, and styling.
- Sheet: A page within an analysis with visuals or text boxes. Choose a sheet type based on how viewers will consume the data: Interactive or Pixel-Perfect Report.
| Sheet Type | Description | When to Use It |
|---|---|---|
| Interactive | For exploration and real-time data analysis, allows users to interact with visuals through filters, parameters, and drill-down actions after the sheet is published as a dashboard. | Ideal for self-service dashboards where users need to dynamically filter and explore data, such as viewing spend by department or analyzing vendor performance trends. |
| Pixel-Perfect Report | Optimized for producing highly formatted, print-ready, and distributable reports that preserve exact layouts and pagination. | Best for operational or formal reporting, such as weekly summaries, vendor invoice listings, or audit-ready exports where consistent formatting matters. |
Filtering & Interactivity
- Filter: A rule limiting which data appears in visuals or sheets.
- Parameter: A dynamic input variable that lets users interactively control filters.
- Control: An on-screen element (dropdown, slider, text box) linked to a parameter.
- Bookmark: A saved dashboard view with specific filters and parameters applied.
Author Pro License
In addition to the Author license, Author Pros include additional AI-supported features.
Business Intelligence with Amazon Q
- Amazon Q: Built-in AI assistant. You can ask it questions or tell it what kind of visual you want. Q interprets your natural language prompts and answers with data-driven business insights.
- Topic: Organizes data and synonyms, so Amazon Q understands your business language to interpret what users mean when they ask questions.
- Synonyms: Additional words or phrases that mean the same thing as your field names. They help Amazon Q understand variations in how users describe data.
- Verified Question: A suggested question generated by AI that you have confirmed returns the right data and visual. Verified questions help guide users to ask effective questions.
- Q&A: A feature that lets users type questions in their everyday or natural language and receive answers in visual form, like “Show approved matter spend by law firm in 2025.”
- Executive Summary: A short overview that highlights important trends, patterns, and takeaways from a dashboard. You can copy the summary and paste it into emails or documents. Sharing/exporting directly is not yet supported.
- Stories: AI-generated, presentation-ready reports that combine dashboard visuals with narrative text.