Step 1
Open Visualization
From the main app, open More > Visualization to launch Data Analysis & Visualization.
Feature
Turn raw data into presentation-ready insights in minutes. Upload a dataset, ask what you want to learn, and get polished analysis with charts and recommendations for decision-making.
Data Analysis & Visualization transforms raw files into decision-ready insights without spreadsheet expertise or manual chart creation. It identifies patterns, extracts key findings, and packages outputs for meetings, board reviews, and strategic planning.
Step 1
From the main app, open More > Visualization to launch Data Analysis & Visualization.
Step 2
Attach CSV, Excel, or structured text data. Sales, surveys, finance, research, and performance datasets all work.
Step 3
Use natural language prompts like “Identify growth opportunities” or “Compare performance by region.”
Step 4
Select slides, dashboard, report, or webpage and receive polished charts, insights, and recommendations.
Request: Analyze this sales data and identify seasonal patterns, top-performing products, and growth opportunities.
Data: 12 months of product sales across multiple categories.
Output: Slide deck with seasonal trend lines, product comparison bars, and strategy recommendations.
Request: Segment these customers by behavior and create profiles for each group.
Data: Purchase history, demographics, and engagement metrics.
Output: Interactive dashboard with scatter clusters, segment distribution, and profile summaries.
Request: Compare our metrics against competitors and highlight where we lead or lag.
Data: Performance metrics from ten companies in the same industry.
Output: Report with radar comparisons, metric-by-metric charts, and positioning insights.
Choose up to five chart types in one analysis so your audience gets trends, comparisons, composition, and relationships in a single narrative.
| Chart type | Best for |
|---|---|
| Bar Charts | Category comparisons, rankings, and side-by-side metrics |
| Line Charts | Trends over time and growth trajectories |
| Pie Charts | Proportions and percentage breakdowns |
| Scatter Plots | Correlations and variable relationships |
| Heat Maps | Pattern intensity across two dimensions |
| Radar Charts | Multi-dimensional and competitive comparisons |
Best for: Executive briefings, client presentations, investor updates
Best for: Monitoring KPIs and team self-service exploration
Best for: Strategy docs, planning, audit-ready documentation
Best for: External sharing and web publication
Quarterly executive review with region comparisons, product trends, customer segments, and action recommendations.
Satisfaction analysis with pain-point themes, customer-type segmentation, and prioritized product improvements.
Competitive positioning map with pricing comparisons, feature heat maps, and differentiation opportunities.
Board-ready monthly review covering revenue trends, expense composition, and cash-flow outlook.
Do: Identify seasonal patterns in sales and recommend inventory adjustments.
Avoid: Analyze this data.
Do: Trends = line, category comparison = bar, composition = pie, relationships = scatter, multidimensional = radar.
Avoid: Use one chart type for every data question.
Do: Executives = slides, ongoing monitoring = dashboard, documentation = report, external sharing = webpage.
Avoid: Use the same format regardless of audience.
Do: Use clear headers, consistent date formatting, and remove irrelevant columns before upload.
Avoid: Upload unstructured exports with mixed date formats and unlabeled fields.