> ## Documentation Index
> Fetch the complete documentation index at: https://docs.shieldbase.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Reporting

> Analyze data into insights and charts in comprehensive reports

## Overview

Transform your data into actionable insights and visualizations. Shieldbase Reporting uses AI to analyze datasets and automatically generate relevant charts, graphs, and analytical insights.

<Info>
  Reporting works best with datasets in tabulated data format. The cleaner the dataset, the more accurate the analysis.
</Info>

## Getting Started

### Video Tutorial - Identify Insights

<Note>
  💡 **Tip**: Adjust video playback speed using the gear icon (⚙️) in the video player. We recommend 0.5x speed for detailed tutorials.
</Note>

<iframe width="100%" height="400" src="https://drive.google.com/file/d/1LtK39bOQG3p9tRXdei8TbE9jBvnlVTo_/preview" frameBorder="0" allow="autoplay; fullscreen" allowFullScreen />

### Create Your First Report

<Steps>
  <Step title="Start New Report">
    Click **New Report** in the Reporting section
  </Step>

  <Step title="Select Data Sources">
    Choose one or multiple datasets from the Library to analyze
  </Step>

  <Step title="Generate Insights">
    Enter a prompt in **Analysis** to generate insights with relevant charts in **Visualization**
  </Step>

  <Step title="Review and Refine">
    Review the generated insights and refine your prompts for better results
  </Step>
</Steps>

## Pro Tip: Insight Discovery

Not sure what insights to generate? Use this powerful prompt:

```text theme={null}
Suggest what insights can be generated from this dataset. Generate the prompt to generate the insights and suggest the chart type to visualize the data. Generate a table for the response.

Column 1: Type of data (descriptive, diagnostic, predictive, prescriptive).
Column 2: Question to be asked in the form of a prompt.
Column 3: Chart type
```

### Video Tutorial - Insight Discovery

<Note>
  💡 **Tip**: Adjust video playback speed using the gear icon (⚙️) in the video player. We recommend 0.5x speed for detailed tutorials.
</Note>

<iframe width="100%" height="400" src="https://drive.google.com/file/d/1GqcmNfMMhR8dPaJ4GubSPtJo8f1bum_V/preview" frameBorder="0" allow="autoplay; fullscreen" allowFullScreen />

## Types of Analysis

<Tabs>
  <Tab title="Descriptive">
    **What happened?**

    Summarize historical data to understand past performance:

    * Sales totals by quarter
    * Customer demographics
    * Product performance metrics
    * Regional distribution
  </Tab>

  <Tab title="Diagnostic">
    **Why did it happen?**

    Identify causes and correlations:

    * Root cause analysis
    * Performance drivers
    * Trend correlations
    * Anomaly detection
  </Tab>

  <Tab title="Predictive">
    **What will happen?**

    Forecast future outcomes:

    * Sales projections
    * Demand forecasting
    * Risk assessment
    * Growth predictions
  </Tab>

  <Tab title="Prescriptive">
    **What should we do?**

    Recommend optimal actions:

    * Resource allocation
    * Process optimization
    * Strategic recommendations
    * Action priorities
  </Tab>
</Tabs>

## Types of Data Visualization

Reporting allows you to transform structured data into insights and visualizations in a report. After selecting one or more datasets from the Library and generating an analysis, Shieldbase renders different chart types based on your data and prompt.

<Tip>
  Choosing the right visualization type for the right data is essential to quickly understand key insights. Data visualization may not show if the chart type is forced to pair with an incompatible dataset.
</Tip>

| Chart Type               | Best Used For                                                                                                                                                                                                                           |
| ------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Table**                | Display raw or aggregated data in rows and columns. Best for detailed views, reference tables, and drill-downs.                                                                                                                         |
| **Bar Chart**            | Compare values across categories (e.g., revenue by region, tickets by status). Supports vertical or horizontal bars.                                                                                                                    |
| **Stacked Bar Chart**    | Show the composition of each category (e.g., revenue by region broken down by product line) while still comparing totals across categories.                                                                                             |
| **Line Chart**           | Visualize trends over time (e.g., daily active users, monthly sales). Ideal for time-series data and monitoring changes.                                                                                                                |
| **Area Chart**           | Similar to line charts but with the area under the line filled. Useful for showing cumulative values and emphasizing volume over time.                                                                                                  |
| **Stacked Area Chart**   | Show how multiple series contribute to a total over time (e.g., traffic by channel over months).                                                                                                                                        |
| **Pie Chart**            | Show the proportion of each category as a percentage of a whole (e.g., market share, budget allocation).                                                                                                                                |
| **Donut Chart**          | A variation of the pie chart with a hollow center, often used to highlight a key metric in the middle while still showing category proportions.                                                                                         |
| **Column Chart**         | A vertical variation of the bar chart, often used interchangeably, to compare discrete categories or time buckets.                                                                                                                      |
| **Scatter Plot**         | Show the relationship between two numeric variables (e.g., marketing spend vs. revenue). Useful for detecting correlations and outliers.                                                                                                |
| **Bubble Chart**         | A scatter plot with an extra dimension represented by bubble size (e.g., x = revenue, y = profit margin, size = number of customers).                                                                                                   |
| **Histogram**            | Show the distribution of a single numeric variable by grouping values into bins (e.g., deal sizes, response times).                                                                                                                     |
| **Heatmap**              | Use color intensity to represent values in a matrix (e.g., performance by region and product, activity by hour and weekday).                                                                                                            |
| **Funnel Chart**         | Represent staged processes such as sales funnels or onboarding flows, illustrating drop-offs between stages.                                                                                                                            |
| **Radar (Spider) Chart** | Compare multiple metrics across different dimensions (e.g., feature scores, department KPIs) on a radial layout.                                                                                                                        |
| **Gauge Chart**          | Highlight a single key metric, often compared against a target or threshold (e.g., SLA adherence, utilization rate).                                                                                                                    |
| **Tornado Chart**        | A specialized bar chart with bars extending left and right from a central axis, typically used in sensitivity or scenario analysis to compare the relative impact of different variables on an outcome.                                 |
| **Gantt Chart**          | Visualize tasks or activities over time, showing start and end dates, durations, and overlaps. Ideal for project timelines, roadmap planning, and tracking dependencies.                                                                |
| **Control Chart**        | Plot a metric over time with upper and lower control limits to monitor process stability and variation. Useful in quality control to detect anomalies or trends that signal process changes.                                            |
| **Org Chart**            | Show hierarchical relationships between people, roles, or entities in a tree-like diagram. Helpful for visualizing organizational structure or ownership relationships.                                                                 |
| **Sankey Diagram**       | Visualize flows and their relative magnitudes between stages or categories (e.g., traffic sources to pages, budget allocations to spending categories). The width of each flow is proportional to its value.                            |
| **Checklist Matrix**     | Display items (e.g., features, requirements, tasks) against a set of categories or entities, indicating presence, completion, or status in a grid format. Useful for audits, feature comparisons, and tracking implementation coverage. |

## Best Practices

<Warning>
  **Data Quality is Critical**: The cleaner the dataset, the easier it is for AI to understand the context, and thus the more accurate the analysis.
</Warning>

### Data Preparation

<Steps>
  <Step title="Clean Your Data">
    Remove duplicates, fix inconsistencies, handle missing values
  </Step>

  <Step title="Structure Properly">
    Use consistent column names, proper data types, clear headers
  </Step>

  <Step title="Validate Accuracy">
    Verify data accuracy before analysis
  </Step>

  <Step title="Document Context">
    Include metadata about data sources and definitions
  </Step>
</Steps>

### Visualization Guidelines

<Tip>
  **Match Chart to Data**: Choosing the right visualization type for the right data is essential to quickly understand key insights. Data visualization may not show if the chart type is incompatible with the dataset.
</Tip>

<Accordion title="Chart Selection Guide">
  **Comparison**: Bar charts, column charts
  **Trends**: Line charts, area charts
  **Composition**: Pie charts, stacked bars
  **Distribution**: Histograms, box plots
  **Correlation**: Scatter plots, bubble charts
  **Geographic**: Maps, regional charts
</Accordion>

## Integration Options

<Info>
  Reporting can be used in **Dashboard**, **Chatbot**, and **Workflows** for comprehensive automation.
</Info>

### Use in Dashboards

<Steps>
  <Step title="Create Reports">
    Build individual reports for different metrics
  </Step>

  <Step title="Add to Dashboard">
    Combine multiple reports in a single dashboard view
  </Step>

  <Step title="Organize Tabs">
    Group related reports into logical sections
  </Step>

  <Step title="Share Access">
    Provide dashboard access to stakeholders
  </Step>
</Steps>

### Use in Workflows

Automate report generation:

* Schedule regular reports
* Trigger based on data updates
* Distribute via email
* Archive for compliance

### Use in Chatbots

Enable conversational analytics:

* Answer data questions
* Generate on-demand reports
* Provide insights interactively
* Explain trends and patterns

## Common Use Cases

<Tabs>
  <Tab title="Sales Analytics">
    * Revenue trends by product/region
    * Sales team performance
    * Customer acquisition costs
    * Pipeline conversion rates
    * Forecast accuracy
  </Tab>

  <Tab title="Marketing Reports">
    * Campaign performance metrics
    * ROI analysis
    * Channel effectiveness
    * Customer segmentation
    * Engagement trends
  </Tab>

  <Tab title="Operations Metrics">
    * Production efficiency
    * Quality control metrics
    * Inventory levels
    * Supply chain performance
    * Resource utilization
  </Tab>

  <Tab title="Financial Analysis">
    * P\&L statements
    * Cash flow analysis
    * Budget vs. actual
    * Cost center analysis
    * Financial ratios
  </Tab>
</Tabs>

## Advanced Features

### Multi-Dataset Analysis

Combine multiple data sources for comprehensive insights:

<Accordion title="Cross-Dataset Analysis">
  1. Select multiple datasets from the Library
  2. AI automatically identifies relationships
  3. Generate unified insights across sources
  4. Create consolidated visualizations
</Accordion>

### Custom Prompts

Examples of effective analysis prompts:

```text theme={null}
"Show me the top 10 performing products by revenue with monthly trend"
```

```text theme={null}
"Identify seasonal patterns in customer behavior and suggest optimal marketing periods"
```

```text theme={null}
"Compare this quarter's performance with the same quarter last year and highlight key differences"
```

## Troubleshooting

<Accordion title="No visualization appears">
  * Check data format compatibility
  * Verify chart type matches data structure
  * Ensure dataset has required columns
  * Try a different visualization type
</Accordion>

<Accordion title="Inaccurate insights">
  * Review data quality and completeness
  * Provide more specific prompts
  * Check for data inconsistencies
  * Verify date formats and ranges
</Accordion>

<Accordion title="Performance issues">
  * Reduce dataset size for initial analysis
  * Use data sampling for large datasets
  * Optimize queries before analysis
  * Consider data aggregation
</Accordion>

## Pro Tips

<CardGroup cols={2}>
  <Card title="Start Broad" icon="expand">
    Begin with high-level insights, then drill down into specifics
  </Card>

  <Card title="Iterate Prompts" icon="repeat">
    Refine your prompts based on initial results for better insights
  </Card>

  <Card title="Combine Views" icon="layer-group">
    Use multiple chart types to tell a complete data story
  </Card>

  <Card title="Regular Updates" icon="clock">
    Schedule automated reports for consistent monitoring
  </Card>
</CardGroup>