Features
Data Analysis & Visualization
Data Analysis & Visualization - Opulent documentation
Data Analysis & Visualization
Turn raw data into presentation-ready insights — from live connector queries to polished charts and spreadsheets
Opulent connects to your live data sources, queries them in natural language, analyzes the results, generates charts, and delivers structured outputs to the Sheets panel, Document panel, or Slides — in minutes, without a BI tool or data analyst in the loop.
What it is
Data Analysis in Opulent spans the full pipeline: connect your data sources, ask questions in plain English, run analysis, build visualizations, and deliver structured outputs — all from a single agent interaction. There is no ETL step, no SQL required, and no dashboard to configure.
Quick Start
Simple Analysis
"How much revenue did we generate in Q4? Break it down by month,
product tier, and top 10 customers by spend."(Requires Stripe connector)
Cross-Source Analysis
"Compare our Stripe MRR growth with pipeline velocity from HubSpot.
Show correlation between deals closing and revenue spikes.
Display as a line chart in the Sheets panel."Bulk Data Processing
"Upload this 50,000-row CSV of customer orders. Find:
- Average order value by region
- Top 20 products by revenue
- Month-over-month growth trend
- Customers with declining order frequency (churn risk)"Visualization Request
"Generate a bar chart of MRR by plan tier for the last 12 months.
Use our brand colors. Export as a PNG for the board deck."Data Sources
Live Connectors
Connect once, query anytime. Opulent pulls live data without requiring exports or manual uploads.
| Connector | What You Can Analyze |
|---|---|
| Stripe | MRR, churn, ARPU, cohort analysis, subscription changes, revenue by plan |
| Salesforce | Pipeline, close rates, rep performance, deal velocity, forecast accuracy |
| HubSpot | Funnel metrics, contact growth, email performance, deal stages |
| Google Analytics | Traffic, conversion, user behavior, source attribution |
| PostgreSQL / MySQL | Any table or view — full SQL-level access via natural language |
| Snowflake / BigQuery | Warehouse queries without writing SQL |
| QuickBooks / Xero | P&L, cash flow, expense breakdown, accounts receivable aging |
| GitHub | Commit velocity, PR cycle time, issue trends, deployment frequency |
| Linear / Jira | Sprint velocity, bug rates, feature lead time, team throughput |
File Uploads
Upload data directly and analyze immediately:
- CSV and Excel files (any size)
- JSON data exports
- PDF reports with embedded tables
- Scanned financial statements (via image understanding)
Analysis Capabilities
Statistical Analysis
- Descriptive statistics: mean, median, distribution, percentiles
- Trend detection: growth rates, seasonality, anomalies
- Correlation analysis across multiple metrics
- Cohort analysis for user or revenue retention
Business Intelligence
- Revenue segmentation by product, region, customer tier
- Funnel analysis from lead to close
- Churn prediction based on usage and behavior signals
- Customer lifetime value modeling
Comparison & Benchmarking
- Period-over-period comparisons (MoM, QoQ, YoY)
- Variance analysis: actual vs. plan vs. prior period
- Competitive benchmarking from public data sources
Visualization
Opulent generates charts and embeds them directly into the Sheets panel, Document panel, or Slides.
Chart Types
| Chart Type | Best For |
|---|---|
| Bar / Column | Comparing categories, rankings |
| Line | Trends over time |
| Area | Cumulative growth, stacked metrics |
| Pie / Donut | Composition, share breakdowns |
| Scatter | Correlation between two variables |
| Heatmap | Performance by two dimensions (e.g., rep × month) |
| Waterfall | Revenue bridges, cost breakdowns |
| Funnel | Conversion analysis |
Generating a Chart
"Create a waterfall chart showing how we went from $850K MRR in January
to $1.1M in June — contributions from new business, expansion, and churn""Generate a cohort retention heatmap for customers who started in 2025.
Month 0 through Month 12 on the axes."Sheets Panel
The Sheets workbench panel displays live tabular data populated by the agent. It is not a static export — results appear incrementally as the agent queries and processes data.
Features
- Columns are auto-detected and named based on the data
- Row filtering and sorting via the panel UI
- Agent can append new rows to an existing sheet
- Export to CSV at any time
Example
"Pull all active subscriptions from Stripe. Group by plan and region.
Show MRR by cohort. Open in the Sheets panel."The agent queries Stripe, transforms the data, and populates the Sheets panel with a live spreadsheet — no export required.
Document Integration
Analysis results can be delivered directly to the Document panel as structured content:
"Analyze our Q4 Stripe data, write a 3-paragraph executive narrative,
embed the key metrics as a formatted table, and add a line chart
showing month-over-month MRR growth"The Document panel receives the written narrative, the data table, and the embedded chart in one response.
Common Use Cases
| Use Case | Data Source | Output |
|---|---|---|
| Revenue Review | Stripe | MRR, churn, ARPU table + line chart |
| Sales Forecast | Salesforce | Pipeline report with close probability |
| Churn Analysis | Stripe + product DB | At-risk customer list |
| Marketing Attribution | Google Analytics + HubSpot | Channel ROI breakdown |
| Engineering Health | GitHub + Linear | Sprint velocity + PR cycle time |
| Financial Close | QuickBooks | P&L, cash flow, AR aging |
| Customer Segmentation | Any CRM | Segments by value, activity, or behavior |
| Competitive Benchmarking | Web research | Feature/price comparison matrix |
Tips for Better Analysis
Be specific about the metric you want:
- ❌
"How are we doing?" - ✅
"What is our MRR growth rate MoM for the last 6 months, broken down by plan tier?"
Specify the time range:
- ❌
"Recent sales data" - ✅
"Q4 2025 (October 1 – December 31)"
Define how you want the output:
- ✅
"Output as a table in the Sheets panel" - ✅
"Include a bar chart and embed it in the Document" - ✅
"Generate a slide deck with one chart per key metric"
Ask for interpretation, not just numbers:
- ✅
"Analyze the data and tell me what's driving churn — don't just show the numbers" - ✅
"Identify the top 3 anomalies and explain what might be causing them"
Common Questions
Do I need to know SQL? No. Describe what you want in plain English. The agent writes and executes the query.
Can I upload my own data files? Yes. Upload CSV, Excel, JSON, or PDF files and analyze them immediately.
How does the agent connect to my database? Via the Connectors panel. You provide credentials once; the agent handles all queries.
Can the agent detect anomalies automatically?
Yes: "Scan our last 12 months of Stripe data and flag anything unusual" produces a list of anomalies with explanations.
Can I save and re-run an analysis? Yes. Save any analysis as a workflow and schedule it (see Scheduled Tasks). The agent re-runs the exact same analysis on the latest data.