Datumry features
One governed workspace from raw data to an owned decision
Datumry combines the work that usually gets split across spreadsheets, dashboard tools, notebooks, and follow-up systems. Start with a guided project or a real business question, then keep the model, evidence, decisions, and recurring updates connected.
Start with files, connections, or a guided template
Create focused projects for SaaS revenue, ecommerce, marketing attribution, agency reporting, or operating performance. Upload CSV, TSV, JSON, or XLSX files, or connect supported spreadsheets, databases, warehouses, Amazon S3 objects including Parquet, business apps, public data URLs, and webhooks.
Prepare data without hiding the rules
Use Clean and organize to review inferred field types and analytical roles, preview repeatable no-code transformation recipes, preserve the original source, and define calculated metrics that remain available to findings, charts, dashboards, and deeper analysis.
Relate sources through a governed semantic model
Confirm joins and cardinality across project sources, inspect relationship diagnostics, create reusable metric and dimension aliases, and keep multi-source analysis bounded to relationships that pass trust checks.
Move through a workspace organized by intent
Findings contains key findings and confidence-ranked recommended charts. Analyze contains Create a chart and Chart Library. Deeper Analysis is a dedicated destination for advanced methods, while Collaborate brings Team access, Tasks, and Sharing together.
Follow an analysis plan tied to the project goal
Datumry ranks useful findings, charts, and deeper analyses for the available model. Purple finding cards are sorted by confidence and can be reviewed as a carousel or opened together. Results retain quantified evidence, source lineage, confidence, warnings, methods, and limitations.
Run David-guided statistics and machine learning
Choose from ten executable methods: time-series forecasting, linear regression, logistic regression, random forest, neural network, gradient boosting, regularized regression, robust regression, k-means clustering, and sentiment analysis. David can recommend a method and explain validation, leakage, uncertainty, tradeoffs, and business impact.
Build dashboards in one live workspace
Drag or add real chart previews, findings, callouts, and section headers from the content tray into a visible dashboard canvas. Reorder, resize, remove, autosave, share, or export without switching between separate choose and arrange steps.
Find missing evidence and keep work owned
Open questions starts with a consequential decision and ranks evidence gaps by estimated value, collection effort, and time. Teammates can comment, mention collaborators, assign follow-ups, set review dates, and track work through a shared activity trail.
Ask David, then approve the action
On eligible plans, David answers questions using the governed project model, helps people navigate Datumry, and assists with advanced methodology choices. It can propose creating a saved chart, creating a metric goal, or enabling monitoring; an authorized user must approve the action before Datumry changes project state.
Keep recurring analysis current
Refresh supported connections manually or on a plan-based schedule. The Always On Analyst compares new project state with its baseline, watches metric goals and data-quality contracts, investigates root-cause contributors, and creates in-app alerts, assigned actions, email notifications, and daily or weekly decision digests when enabled.
At a glance
- Guided templates and no-code data cleanup
- Ten David-guided deeper-analysis methods
- Confidence-ranked findings and a reusable Chart Library
- Live dashboard canvas, sharing, exports, and collaboration
See the complete workflow with synthetic data
Open the public sample analysis to follow a governed source through quality checks, findings, a forecast, customer segments, and an owned decision summary.