Analysis Widget

Introduction

The Analysis Widget enables users to view and interact with Adhoc Analysis reports directly on the dashboard. Users can explore data in a flexible pivot-table format or instantly visualize it as charts.

If a new report is created within the widget, it is automatically saved in the Adhoc Analysis section for future use.

Purpose

The Analysis Widget provides a user-driven analytical experience where data can be grouped, aggregated, filtered, and visualized across multiple dimensions.
It is ideal for answering complex business questions that require multi-level analysis without pre-defining every view.

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Steps to Create an Analysis Widget

1. From the left vertical menu, click the Analysis Widget icon.

   

2. An empty container appears on the canvas.

   

3. Click the Show Field List icon to open the Analysis Selection modal.

   

4. Configure your pivot structure:

   Area	Description	Example
   Datasets & Available Columns	Select the dataset. Columns appear below.	dssuperstore.ds
   Filters	Restrict data before analysis.	ShipMode = First Class
   Rows	Defines pivot rows.	Country, City
   Columns	Defines pivot columns.	Category, Sub-Category
   Values	Numerical fields with aggregation (Sum, Avg, Count).	Sales, Profit

   

5. Click Preview to validate results.

6. Save your configuration using Save As.

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Advanced Options

Subtotals & Grand Totals

Flexible options for showing or hiding totals in pivot tables.

• Show – Display totals for rows and/or columns.

• Do not show – Hide all totals.

• Show rows only – Show totals only for rows.

• Show columns only – Show totals only for columns.

• Positioning: Place totals at the Top or Bottom (default).

  

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Conditional Formatting

Apply styles to values based on predefined rules. Helps highlight trends, outliers, and key insights.

• Value – Select a field or All Values. Use operators: Less Than, Greater Than, Equal To, Not Equal To, Between, Not Between.
• Apply to Grand Total – Extend rules to totals.
• Format – Customize font family, size, color, background color, and number preview.
• + Add Condition – Add multiple rules.

Actions:

• Apply – Save rules.
• Cancel – Discard.

Example: Highlight Sales values Greater Than 10,000 with a teal font and yellow background.

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Number Formatting

Control how numeric values appear for better readability and reporting consistency.

• Values – Apply to selected fields or All Values.
• Format Type – Number, Currency, Percentage, or Custom.
• Grouping – Enable/disable thousand separators.
• Decimal Places – Set decimals.
• Custom Format – Define custom strings (e.g., FY##: 0.00M).

Actions:

• Apply – Save changes.

• Cancel – Discard.

  

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Chart Options

Switch pivot data into different charts for faster insights.

Available Chart Types:
Select from Column, Bar, Line, Area, Scatter, Polar, Stacked Column, or More as per your analysis needs.

Additional Options:

• Multiple Axis – Plot values on dual Y-axes.
• Show Legend – Toggle legend visibility.

How to Use:

1. Click the Chart Type icon.
2. Select a chart.
3. Use Multiple Axis/Legend options.
4. Switch back anytime with Show Table.

Example: Compare Sales vs. Profit with a Column chart + Multiple Axis, or show segment contribution with a Stacked Column chart.

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Export / Download

Export results for offline use: PDF, Excel, CSV, PNG, JPEG, SVG.

• How to Use: Click the Download icon → choose format.

• Benefit: Share insights or perform further analysis outside AIV.

  

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Saving Your Work

• Save As – Create a new copy.

• Always save before previewing to avoid losing changes.

  

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Use Cases

Use Case	Example	Features Used
Sales Performance	Analyze revenue by Region (Columns) and Category (Rows).	Rows, Columns, Values, Totals
Financial Budgeting	Compare Actual vs. Budget across Departments.	Custom Calculations, Values
HR Headcount	Distribution by Location (Columns) and Job Level (Rows).	Rows, Columns, Count
Web Traffic	Sessions by Traffic Source and Landing Page.	Rows, Columns, Chart View
Survey Data	Avg. Satisfaction by Age Group & Gender.	Rows, Columns, Average, Subtotals

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Example Scenario: Product Sales by Region

Objective: Identify which product categories perform best by region.

Dataset (SalesData):

Region	Category	UnitsSold
North	Electronics	500
North	Apparel	300
West	Electronics	750
West	Apparel	450

Steps:

1. Add an Analysis Widget.
2. Open Field List.
3. Drag Category → Rows, Region → Columns, UnitsSold → Values (Sum).
4. Preview the pivot table.
5. Switch to Stacked Column Chart for visual comparison.
6. Export results to Excel.

Outcome: Start with a pivot table, switch to chart view for insights, and export results—all in a few clicks.

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