Move from raw survey or study data to a defensible first look.
Use Amridata for descriptive exploration: check data quality, inspect distributions, compare groups, visualize relationships, and document early findings before moving into specialized inferential analysis when needed.
Use the data you already export.
Amridata is file-first: bring a table from the system you already use, then inspect, clean, visualize, and explain it.
Audit the dataset
Profile types, missing values, unique counts, and duplicates before running more formal analyses.
Explore distributions + groups
Use histograms, box plots, bar charts, scatter plots, heatmaps, and descriptive statistics for exploratory analysis.
Document early observations
Save visuals and summaries in a report that can support team discussion or analysis planning.
Files and fields research teams can explore
The exact columns depend on your source system. These examples describe the kinds of tabular exports the workspace is designed to handle.
Four steps from export to explanation
No platform connector is required for the core workflow. Start from CSV, XLSX, or JSON data you are authorized to use.
- 1
Import a working copy
Keep your source data and use an analysis-ready copy.
- 2
Profile + clean
Check structure, types, missingness, duplicates, and labels.
- 3
Explore
Use descriptive statistics and appropriate charts to understand the data.
- 4
Escalate when needed
Use specialized statistical methods when your research question requires inference, modeling, or formal hypothesis testing.
Use business questions to choose the next analysis.
A good workflow starts with the decision you need to support, then picks the chart, cleaning step, or AI question that fits it.
- Which variables have missing data?
- What does the distribution of this measure look like?
- How do groups differ descriptively?
- Which variables appear suitable for a scatter plot or box plot?
Features that support the workflow
Use only the parts that match your question; the product does not force every dataset into the same analysis.
Research analytics questions
What Amridata does—and what it does not pretend to be.
Is Amridata intended for inferential statistics?+
Its strongest current use is descriptive and exploratory analysis, cleaning, visualization, and communication. Specialized inferential work may require dedicated statistical software.
Can I compare multiple groups visually?+
Yes. Depending on the data, grouped bar charts, stacked charts, box plots, heatmaps, and other supported chart types can help compare groups descriptively.