Data View is your first stop after loading a file. Before running any analysis, you need confidence that the data loaded correctly — the right number of rows, the right column names, sensible values in every cell.
It gives you a full-featured preview table with a dual-handle row range slider, automatic missing value detection, value label decoding, and a complete column inventory.
Real-world data is rarely clean. Surveys come back with typos, missing answers, inconsistent codes, and rows you didn't expect. Data Management gives you a friendly toolkit to fix these issues before you start analysing.
Every action is reversible — there's an Undo button that keeps your last 10 changes, so you can experiment freely without fear of breaking your data.
Descriptive analysis answers basic but essential questions: How many people answered each option? What's the average? Where do most respondents fall? Before you run any fancy statistical test, you need to know what's actually in your data.
This module gives you five ways to summarise: Data Quality (missing values, duplicates, constants, and outliers for every variable), Frequency (counts and percentages), Cross-Tabulate (contingency tables with chi-square), Summary Statistics (mean, median, SD, range, skewness, kurtosis), and Publication Table (grouped characteristics table — the academic "Table 1").
Descriptive statistics tell you what's in your sample. Inferential statistics let you draw conclusions about the wider population — testing whether observed differences are real, or just chance fluctuations.
Whether you want to compare two groups, examine relationships between variables, or build a model that predicts outcomes, this module has the right tool for the job.
A well-designed chart can communicate something a table never could. This module gives you 15+ chart types — each with smart defaults so you can produce something publishable in seconds, plus a full customisation panel for titles, axis labels, colours, fonts, and backgrounds.
You can build a multi-chart dashboard with multiple charts side-by-side and cross-filtering — clicking any bar, slice, or point dims related data across all other charts simultaneously. Share the dashboard as a live link (no account to view) or download as interactive HTML.
To tell a narrative story with your charts, use Data Canvas — add any chart directly to a slide deck with plain-language headlines and context.
If you're using a multi-item questionnaire (like a satisfaction scale, a personality inventory, or a stress measure), you need evidence that the items are actually measuring the same thing. That's what scale validation is for.
This module helps you check internal consistency, identify underlying themes, and reduce many variables into fewer composites — three of the most common steps in psychometric and survey research.
One of the most common questions in research is "How big a sample do I need?" Too few participants and your results won't be reliable; too many and you waste time and money.
This module gives you a calculator for the most common study designs. You tell it the size of effect you expect to find and the level of confidence you need; it tells you the minimum number of participants required.
Numbers only tell part of the story. When you've collected interview transcripts, open-ended survey responses, or free-text comments, you need tools that can handle words rather than numbers.
This module helps you organise text data, identify recurring themes, count word frequencies, and explore how concepts relate to each other — the kind of work that traditionally takes weeks of manual coding.
You've run your analyses, made your charts, and spotted some patterns. Now what? The hardest part of any analysis project is pulling everything together into a story that makes sense to your audience.
Sense Making is an AI-assisted workspace that helps you synthesise findings across modules — so your final report or presentation flows naturally from the data, not as a disconnected list of test results.
Data Canvas turns your analysis outputs into a shareable, scrollable narrative. Add slides from any module (charts, tables, participant quotes, or narrative text), write plain-language insight headlines, and publish as a public link anyone can read in their browser — no account, no software, no design skills needed.
It bridges the gap between statistical output and human communication. Where dashboards enable interactive data exploration, Data Canvas tells the story of what the data means.
Analysis projects often span multiple sessions. You clean your data on Monday, run your descriptives on Tuesday, build your model on Wednesday. Without session management, that means re-uploading and re-cleaning every time.
Save your entire workspace — data, variable labels, value
labels, action history, and overrides — into a single
.analyZ file. Reload it any time to continue
exactly where you left off.
.analyZ file is a portable record of
your work that you can share with collaborators or come back
to months later.
Connect AnalyZ directly to a live survey platform — no file download, no manual export. Paste any URL from your survey platform and AnalyZ pulls the data straight into your workspace, complete with variable labels, value codes, and multilingual question text.
Supported platforms include KoBo Toolbox, ODK Central, REDCap, Google Sheets (published as CSV), and any REST endpoint returning JSON or CSV.
Before loading, a picker shows all variables with their labels. Search, filter, and select only the variables you need. This keeps your workspace clean and avoids loading system metadata or fields you don't need for your analysis.
Once connected, a ↻ refresh button appears under Connected sources in the sidebar. Click it to pull the latest submissions at any time. Your token is stored in browser session memory only — if you close and reopen the browser, you will be prompted to re-enter it.