Skip to content
Documentation

What Querri Can Do

This reference lists everything you can accomplish with Querri’s AI agent. Simply describe what you want in natural language, and the agent handles the technical details.

Data Discovery & Loading

Section titled “Data Discovery & Loading”

Finding Data in Your Library

Section titled “Finding Data in Your Library”

What you can do:

  • Search for data by topic or keywords
  • Load specific data sources by name
  • Automatically find relevant sources for your analysis

How to ask:

  • “Analyze my sales data”
  • “Load the customer database”
  • “I need Q4 revenue information”

How it works:

  • Agent searches your entire Library
  • Matches sources based on names, descriptions, and content summaries
  • Selectively loads 1-2 most relevant sources to stay focused
  • Can load additional sources if you specifically request them

Loading Specific Sources

Section titled “Loading Specific Sources”

What you can do:

  • Load a particular file or connector by name
  • Combine multiple specific sources in one project
  • Reload updated data

How to ask:

  • “Load the Q4_Sales_Report source”
  • “I want both the customers and transactions data”
  • “Refresh the sales data”

Data Investigation

Section titled “Data Investigation”

Understanding Your Data

Section titled “Understanding Your Data”

What you can do:

  • Get column statistics (min, max, average, counts)
  • See unique values in categorical columns
  • Understand data types and formats
  • Preview data samples

How to ask:

  • “What’s in this data?”
  • “Show me statistics for the revenue column”
  • “What are the unique categories?”
  • “How many rows and columns do I have?”

Querying and Exploring

Section titled “Querying and Exploring”

What you can do:

  • Run custom queries to investigate data
  • Find specific values or patterns
  • Count, sum, or aggregate for exploration
  • Identify data quality issues

How to ask:

  • “What are the top 10 customers by spending?”
  • “Show me all the different product categories”
  • “How many null values are in the price column?”
  • “Find duplicate customer IDs”

Data Transformation

Section titled “Data Transformation”

Filtering and Selecting

Section titled “Filtering and Selecting”

What you can do:

  • Filter rows based on conditions
  • Select specific columns
  • Remove unwanted data
  • Extract subsets

How to ask:

  • “Filter to transactions from 2024”
  • “Show only premium customers”
  • “Remove rows where revenue is null”
  • “Give me just the name, date, and amount columns”

Aggregating and Grouping

Section titled “Aggregating and Grouping”

What you can do:

  • Sum, average, count, min, max
  • Group by categories, time periods, or combinations
  • Calculate percentages and ratios
  • Create summary tables

How to ask:

  • “Total revenue by month”
  • “Average order value by customer segment”
  • “Count of orders per product category”
  • “Sum sales grouped by region and product”

Joining Data

Section titled “Joining Data”

What you can do:

  • Combine multiple datasets
  • Match records across sources
  • Merge based on common fields
  • Create unified views

How to ask:

  • “Join customers with their orders”
  • “Merge sales and costs on product ID”
  • “Combine all three datasets”
  • “Match transactions to customer info”

Calculating New Fields

Section titled “Calculating New Fields”

What you can do:

  • Add derived columns
  • Perform calculations across columns
  • Create conditional fields
  • Apply formulas

How to ask:

  • “Add a profit column (revenue minus cost)”
  • “Calculate days since last purchase”
  • “Create a category for high/medium/low value customers”
  • “Add a column with 10% markup”

Sorting and Ranking

Section titled “Sorting and Ranking”

What you can do:

  • Sort by any column
  • Rank items
  • Find top/bottom N
  • Order by multiple criteria

How to ask:

  • “Sort by revenue descending”
  • “Show me the top 20 products”
  • “Rank customers by purchase frequency”
  • “Order by date then amount”

Visualizations

Section titled “Visualizations”

Chart Types Available

Section titled “Chart Types Available”

Interactive Charts:

  • Line charts - trends over time
  • Bar charts - comparisons between categories
  • Scatter plots - relationships between variables
  • Area charts - cumulative trends
  • Pie charts - proportional breakdowns
  • Histograms - distributions
  • Box plots - statistical distributions
  • Heatmaps - matrices and correlations
  • Bubble charts - three-variable relationships

Specialized Visualizations:

  • Wordclouds - text frequency
  • Venn diagrams - set overlaps
  • Geospatial maps - location data

How to ask:

  • “Create a line chart of monthly revenue”
  • “Show me a bar chart comparing sales by region”
  • “Plot customer age vs. lifetime value as a scatter”
  • “Make a pie chart of market share”

Chart Customization

Section titled “Chart Customization”

What you can do:

  • Change chart types
  • Modify colors and styling
  • Add titles and labels
  • Adjust axes and scales
  • Include trend lines
  • Add annotations

How to ask:

  • “Make that a line chart instead of bars”
  • “Add a trend line”
  • “Use a log scale on the Y axis”
  • “Change the title to ‘Q4 Performance’”
  • “Add labels to each point”

Professional Styling

Section titled “Professional Styling”

All charts automatically include:

  • Querri’s professional color palette
  • Clear, readable fonts
  • Responsive sizing
  • Interactive features (zoom, pan, hover details)
  • Proper axis labels and legends

Advanced Analytics

Section titled “Advanced Analytics”

Time Series Forecasting

Section titled “Time Series Forecasting”

What you can do:

  • Predict future values
  • Generate confidence intervals
  • Forecast multiple time series at once
  • Automatic model selection (ARIMA/Prophet)

How to ask:

  • “Forecast revenue for the next 3 months”
  • “Predict customer growth through year-end”
  • “Show me projected sales with confidence intervals”
  • “Generate forecasts for each product category”

Typical workflow:

  1. Prepare time series data
  2. Request forecast
  3. View results with confidence bands
  4. Visualize historical + predicted values

Statistical Analysis

Section titled “Statistical Analysis”

What you can do:

  • Calculate correlations
  • Identify trends
  • Find outliers
  • Perform statistical tests
  • Analyze distributions

How to ask:

  • “What’s the correlation between marketing spend and sales?”
  • “Find outliers in transaction amounts”
  • “Show me the distribution of customer ages”
  • “Is there a trend in monthly growth?”

Pivot Tables

Section titled “Pivot Tables”

What you can do:

  • Create multi-dimensional summaries
  • Cross-tabulate data
  • Analyze by multiple categories

How to ask:

  • “Create a pivot table of sales by region and product”
  • “Show revenue by month and customer segment”
  • “Cross-tab orders by day of week and hour”

Geospatial Analysis

Section titled “Geospatial Analysis”

What you can do:

  • Create maps with location data
  • Visualize regional patterns
  • Plot points on maps
  • Color regions by values

How to ask:

  • “Map sales by state”
  • “Show customer locations on a map”
  • “Create a heatmap of revenue by region”
  • “Plot store locations”

Network Analysis

Section titled “Network Analysis”

What you can do:

  • Visualize relationships and connections
  • Create network diagrams
  • Analyze relationship patterns

How to ask:

  • “Show the relationship network between accounts”
  • “Create an org chart from this data”
  • “Visualize customer referral connections”

Data Cleaning

Section titled “Data Cleaning”

Handling Duplicates

Section titled “Handling Duplicates”

What you can do:

  • Remove duplicate rows
  • Identify duplicates before removing
  • Keep first/last occurrence
  • Deduplicate based on specific columns

How to ask:

  • “Remove duplicate rows”
  • “Find duplicate customer IDs”
  • “Keep only the first transaction per customer”
  • “Remove duplicates based on email address”

Dealing with Missing Values

Section titled “Dealing with Missing Values”

What you can do:

  • Fill missing values
  • Remove rows with nulls
  • Forward-fill or back-fill
  • Replace with mean/median/mode

How to ask:

  • “Fill missing prices with the median price”
  • “Remove rows where revenue is null”
  • “Forward-fill the category column”
  • “Replace null values with zero”

Standardizing Formats

Section titled “Standardizing Formats”

What you can do:

  • Standardize date formats
  • Clean text (trim whitespace, fix casing)
  • Convert data types
  • Parse structured data

How to ask:

  • “Convert all dates to YYYY-MM-DD format”
  • “Trim whitespace from product names”
  • “Convert the amount column to numbers”
  • “Standardize phone numbers”

Exporting & Sharing

Section titled “Exporting & Sharing”

Excel Exports

Section titled “Excel Exports”

What you can do:

  • Create professionally formatted Excel files
  • Include multiple sheets
  • Apply styling and formatting
  • Add headers and colors

Features automatically included:

  • Blue headers with white text
  • Alternating row colors for readability
  • Auto-sized columns
  • Number formatting
  • Multiple sheets for complex exports

How to ask:

  • “Export this to Excel”
  • “Create an Excel file with these three tables”
  • “Generate a formatted Excel report”

CSV Exports

Section titled “CSV Exports”

What you can do:

  • Download data as CSV
  • Export for use in other tools
  • Archive analysis results

How to ask:

  • “Export this as CSV”
  • “Download the filtered data”

Dashboards

Section titled “Dashboards”

What you can do:

  • Combine multiple visualizations
  • Create shareable dashboards
  • Optimal layouts (4-12 widgets)
  • Automatic widget sizing and positioning

How to ask:

  • “Create a dashboard from these charts”
  • “Make a dashboard with sales visualizations”
  • “Build a dashboard for the executive team”

The agent will:

  • Analyze your project
  • Select the best visualizations
  • Suggest an optimal layout
  • Create a 4-12 widget dashboard

Highlighting Insights

Section titled “Highlighting Insights”

What you can do:

  • Show focused data summaries in chat
  • Highlight key metrics
  • Call out important findings

How to ask:

  • “Show me just the top 5 customers”
  • “Highlight the key findings”
  • “Display a summary of these results”

How to Ask for What You Need

Section titled “How to Ask for What You Need”

The Pattern

Section titled “The Pattern”

Most requests follow this pattern:

[Action] + [What] + [How/Where/When]

Examples:

  • “Show me [action] revenue [what] by month [how]”
  • “Filter [action] to California customers [what] from 2024 [when]”
  • “Create [action] a line chart [what] of daily signups [how]“

Starting Simple

Section titled “Starting Simple”

Begin with a basic request and refine:

1. "Analyze my sales data" → Agent loads data
2. "Show me 2024 only" → Agent filters
3. "Break that down by month" → Agent aggregates
4. "Create a chart" → Agent visualizes

Being Specific

Section titled “Being Specific”

More specific requests get better results:

  • ❌ “Show me the data”

  • ✅ “Show me monthly revenue for 2024”

  • ❌ “Make a chart”

  • ✅ “Create a line chart of revenue trends by month”

Common Patterns

Section titled “Common Patterns”

Exploration:

  • “What’s in this data?”
  • “Show me the first 100 rows”
  • “What are the column names?”

Analysis:

  • “Calculate total revenue by region”
  • “Find the top 10 customers”
  • “Show me year-over-year growth”

Visualization:

  • “Create a bar chart of [metric] by [dimension]”
  • “Plot [X] vs. [Y] as a scatter”
  • “Show [metric] over time as a line chart”

Forecasting:

  • “Forecast [metric] for the next [N] periods”
  • “Predict [metric] through [date]“

Limitations and Best Practices

Section titled “Limitations and Best Practices”

Data Size

Section titled “Data Size”
  • Optimal: Datasets under 100K rows process fastest
  • Large data: Automatically uses streaming for efficiency
  • Best practice: Aggregate large datasets before visualizing

Visualization

Section titled “Visualization”
  • Chart complexity: Best with < 10K points; aggregate larger datasets first
  • Dashboard widgets: 4-12 widgets recommended for readability

Forecasting

Section titled “Forecasting”
  • Minimum data: At least 20 historical data points
  • Best results: Consistent time periods with clear patterns
  • Multiple series: Can forecast many series at once

Multi-Step Operations

Section titled “Multi-Step Operations”

Some operations require multiple steps:

  • Forecast visualization: Forecast → Sort → Chart (3 steps)
  • Multi-source analysis: Load → Load → Join → Analyze
  • Clean and analyze: Clean → Transform → Visualize

The agent handles these sequences automatically.

See Also

Section titled “See Also”