Upload a CSV and Ask Questions About Your Data

Upload structured spreadsheet data and ask questions in plain English to compare values, calculate statistics, identify trends, and summarize results.

VizMint should show the fields, filters, calculations, and source rows used to create each answer so users can review how the conclusion was produced.

Supports structured .csv and .xlsx files. Public examples use synthetic data. Review VizMint's current privacy and retention policy before uploading sensitive information.

Drop your CSV or Excel file here to generate instant insightsDrag and drop your file here, or click to browse
Demo

See how questions turn into source-grounded answers

Use the fixed preview below to switch between the source spreadsheet and a dashboard sample. Open the full demo in a new tab for every KPI and chart.

Ask Questions About CSV

Interactive preview from the sample business dataset

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Switch preview

Total Records

48

rows in sample

Total Gross Revenue

1,544,201

sum of Gross Revenue

Total Target Revenue

1,504,652

sum of Target Revenue

Gross Revenue vs Target Revenue

Grouped by Date

Full dashboard with all KPI details and 6 charts is on the demo page.

Open full demo

What the live demo includes

  • Source rows with date, product, region, revenue, cost, and quantity
  • Auto-detected KPI cards for revenue, orders, and contribution
  • Comparison charts by product, region, and sales representative
  • Trend charts showing revenue and cost over time
  • Distribution and scatter views when numeric fields exist
  • Switch between Spreadsheet and Dashboard tabs in the live preview
  • Open the full demo in a new tab for all generated charts

The sample contains 48 business records across 4 products and 4 regions. Charts and KPI cards are generated from the same JSON dataset.

Sample totals: $1,439,545 revenue, $631,847 cost, 4,072 orders, and $354 average order value.

Why This Workflow Is Useful

The Decision It Supports

Ask a business question and receive a source-grounded answer that exposes its fields, filters, calculation, and supporting rows.

Why the Result Can Be Trusted

Natural-language analysis is useful only when the answer can be verified. Users need to see the fields, filters, calculations, and source rows used, plus any ambiguity in the question.

Example Dataset

The sales sample contains 48 records across 4 products with $1,439,545 in revenue — ready to answer grouped, trend, and comparison questions.

Why VizMint is different from a generic template

  • Begin with the structured file the user already has.
  • Explain required fields before upload and show detected mapping after upload.
  • Display formulas, reporting scope, exclusions, and missing-field behaviour beside the result.
  • Use one synthetic dataset across the live preview, expected results, KPI cards, and charts.
  • Connect headline metrics to the records or grouped table that explain them.
  • State plan, export, privacy, integration, and automation details only when they are available in the current product.

The workflow is designed around traceable, disciplined answers rather than confident-sounding chat.

Explore Spreadsheet Data Without Writing Formulas or Queries

Users often know the business question they want to answer but do not know which pivot table, formula, or chart to build. A conversational data workflow lets them ask a direct question and receive a source-based answer.

The page must prove more than generic AI chat. It should show a real uploaded file, a natural-language question, the fields used, retrieved rows, calculations, and a transparent answer.

This workflow helps answer questions such as:

  • Which product generated the most revenue?
  • How do revenue and cost compare by region?
  • Which month had the highest sales?
  • What is the average order value?
  • Are there unusual values or outliers?
  • Which representative or category performed best?
  • See How the Source File Becomes a VizMint Output

    Follow the same dataset from source rows to the generated dashboard preview. The spreadsheet table, KPI cards, and charts all come from one JSON sample, so every visible result can be checked against the source.

    Before: Structured Source Data

    5 of 48 rows

    The source preview highlights the exact columns and representative rows used in the analysis.

    DateQuarterProductRegionGross Revenue
    2025-07-01Q3 2025Analytics ProNorth27,060
    2025-07-01Q3 2025Dashboard PlusSouth25,200
    2025-07-01Q3 2025Reporting SuiteEast19,270
    2025-07-01Q3 2025ImplementationWest14,430
    2025-08-01Q3 2025Analytics ProSouth29,756

    After: Generated VizMint Output

    The finished example is generated from the sample dataset rather than an unrelated mockup or stock image.

    Revenue$1,439,5454,072 orders
    Products44 regions
    Avg Order Value$3544 representatives

    Gross Revenue vs Target Revenue

    Grouped by Date

    Columns to Include in Your File

    VizMint works best when every column has one clear heading and each row represents one consistent record.

    Supported File Structures

    Standard tabular CSV

    • • Date
    • • Product
    • • Region
    • • Revenue
    • • Cost
    • • Quantity

    Structured Excel worksheet

    • • One header row
    • • One record per row
    • • Consistent data types
    ColumnRequirementExamplePurpose
    Clear Unique HeadersRequiredRevenueAllows field identification
    DateRecommended2026-06-01Supports trends and period comparisons
    Numeric MeasuresRequired for calculationsRevenue, Cost, QuantitySupports totals, averages, and comparisons
    Category FieldsRecommendedProduct, Region, TeamSupports grouping
    Stable IDsOptionalOrder IDSupports distinct counts and row references
    Text DescriptionOptionalEnterprise renewalProvides context but may not be used for numeric calculations

    What VizMint Can Generate

    Relevant Rows Retrieved

    Rows matching the question or filter.

    Fields Used

    Columns used in the calculation.

    Grouped Summary

    Totals or averages by selected category.

    Two-Column Comparison

    Comparison between two numeric fields.

    Trend Result

    Change across valid time periods.

    Outlier Review

    Unusually high or low values under a documented method.

    Answer Confidence or Limitation

    Visible note when data is incomplete or ambiguous.

    Follow-Up Context

    Ability to ask a related question without re-uploading.

    Charts and Visualizations

    Chart or OutputRequired FieldsBusiness Question
    Supporting TableFields and source rowsWhich records support the answer?
    Comparison Bar ChartCategory and numeric measureHow do groups compare?
    Trend ChartDate and measureHow is the metric changing?
    Scatter PlotTwo numeric fieldsIs there a visible relationship?
    Distribution ChartNumeric fieldHow are values distributed?
    Summary CardCalculated statisticWhat is the direct answer?

    How to Use This Workflow

    STEP 1

    Prepare the File

    Use clear headers, one record per row, consistent dates, and numeric values stored as numbers.

    STEP 2

    Upload the File

    Select the CSV or Excel file using the page's upload control.

    STEP 3

    Choose the Worksheet

    For multi-sheet workbooks, choose the sheet containing the relevant data table.

    STEP 4

    Confirm Field Mapping

    Review the detected fields and map any column VizMint could not identify confidently.

    STEP 5

    Review the Preview

    Check dates, numbers, categories, missing values, and record counts before generation.

    STEP 6

    Generate the Output

    Create the supported dashboard, report, presentation, chart, or answer.

    STEP 7

    Review and Export

    Review calculations and limitations, then save, share, or export using the options available in the active plan.

    How the Calculations Work

    MetricFormula or MethodRequired FieldsImportant Rule
    SumTotal of valid numeric valuesNumeric fieldExclude invalid and missing values.
    AverageSum ÷ valid record countNumeric fieldDo not include missing values as zero.
    Distinct CountCount of unique valid IDsStable identifierFormatting variations can create false duplicates.
    Period ComparisonCurrent-period metric − previous-period metricDate and measureRequires comparable periods.
    CorrelationStatistical relationship between two numeric fieldsTwo numeric fieldsDoes not prove causation and requires enough valid observations.

    What This Workflow Requires and Does Not Automatically Do

    • Missing fields cannot be invented.
    • Ambiguous questions may require clarification.
    • Correlation does not establish causation.
    • Large, unstructured, or poorly formatted files may require cleaning.
    • Free-text documents are different from structured CSV analysis.
    • Answers should remain traceable to source fields and rows.
    • Sensitive file contents must not be sent to analytics systems.

    Common Data Problems and How to Fix Them

    ProblemRecommended Fix
    Headers are blank or duplicatedUse short unique names.
    Numbers are stored as textConvert them to numeric values.
    Multiple tables exist on one sheetKeep one rectangular table per worksheet.
    Summary rows are mixed with detailRemove totals before analysis.
    Dates use inconsistent formatsStandardize dates.
    The question is vagueClarify the metric, filter, group, or period.

    Who This Workflow Is For

    • Business users without SQL or BI experience
    • Analysts exploring unfamiliar files
    • Sales and marketing teams
    • Finance and operations managers
    • Consultants reviewing client data

    Common Use Cases

    • Quick file exploration
    • Metric comparison
    • Trend identification
    • Grouped summaries
    • Outlier review
    • Plain-English data explanation
    • Follow-up analysis

    Why Use VizMint for This Workflow?

    • Start with the user's business question.
    • Show the calculation and supporting rows.
    • Use field-name citations rather than unsupported narrative.
    • Handle ambiguous or missing data transparently.
    • Combine conversational analysis with charts and summaries.

    Share and Export Your Results

    Available options depend on the live VizMint plan. The final page should list only verified capabilities, such as saving the analysis, downloading chart images, exporting PDF or PowerPoint files, creating a shareable link, refreshing with updated data, or removing branding on eligible plans.

    Do not publish a plan comparison until product and billing owners confirm every feature.

    Recommended Supporting Articles

    • • How to Ask Questions About CSV Data
    • • How to Compare Two Spreadsheet Columns
    • • How to Find Trends and Outliers in a Spreadsheet
    • • Scatter Plot vs Correlation: What Each One Tells You

    Frequently Asked Questions

    Choose the Right Approach

    Excel alone is enough when

    • The dataset is small and the report is genuinely one-off.
    • One spreadsheet owner can safely maintain formulas, pivots, and ranges.
    • The audience does not need a repeatable upload-to-output workflow.

    A traditional BI tool is a better fit when

    • The organization needs governed models, live connectors, row-level security, and enterprise distribution.
    • A data team can maintain transformations and a semantic layer.

    VizMint is a strong fit when

    • The starting point is a structured CSV or Excel file.
    • The user needs a guided workflow without manually building every formula and chart.
    • Clear field requirements, transparent calculations, reproducible samples, and shareable outputs matter.

    VizMint analyzes exports; it does not replace the accounting, CRM, help-desk, HR, warehouse, advertising, or project-management system that produced them.

    Ready to Use Your Data for Ask Questions About CSV?

    Upload a structured CSV or Excel file, review the detected fields, and generate the workflow-specific output described on this page.