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Catalyst Analytics R: Getting Started

Start using Catalyst Analytics R with a controlled example.

ProductCatalyst Analytics RVerified version1.2.0ComponentAccounting, Browser Demo Parity, Canonical JSON Export, Comparison, Data Intake, Dataset Validation, Derived Indicators, Indicator Registry, Package Validation, Reproducible Reports, Sensitivity, Snapshots, Source Metadata, Stress Testing, Uncertainty, WorkspacesUpdatedJuly 17, 2026Reading time18 minutes
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Catalyst Analytics R · Getting Started

Reproducible R data intake, metadata, validation, indicators, comparison, uncertainty, sensitivity, stress, accounting, workspaces, snapshots, reports, and export.

Audience: product users, administrators, reviewers, and integrators.

Last verified version: 1.2.0

Reading time: 18–30 minutes

Status: Published support documentation.

Purpose

This guide provides a safe first run of Catalyst Analytics R. It explains the product role, the main feature surface, the synthetic demonstration dataset, how to recognize a valid result, and when human or expert review is required.

Capability overview

  • Data Intake
  • Source Metadata
  • Dataset Validation
  • Indicator Registry
  • Derived Indicators
  • Comparison
  • Uncertainty
  • Sensitivity
  • Stress Testing
  • Accounting
  • Workspaces
  • Snapshots
  • Reproducible Reports
  • Canonical JSON Export
  • Browser Demo Parity
  • Package Validation

Prerequisites

  • A modern supported browser or runtime
  • The current installed product and service version
  • A new demonstration workspace
  • No confidential, personal, credential, or production information
  • A named reviewer for consequential output

Sample data

This article uses a fictional Resilient Community Retrofit Program. The files contain one demonstration row for every documented feature, so each capability can be tested without private or production data.

Download CSV feature examples · Download JSON workspace example

Preview

# Feature Sample action Expected result Classification
1 Data Intake read the feature-example CSV or JSON a governed R data object synthetic-demo
2 Source Metadata attach publisher, URL, license, citation, retrieval, field, and unit metadata a source-aware dataset synthetic-demo
3 Dataset Validation check required fields, types, missingness, units, and duplicates a validation report synthetic-demo
4 Indicator Registry register annual energy savings a reusable indicator definition synthetic-demo
5 Derived Indicators calculate baseline minus retrofit kWh derived values with method metadata synthetic-demo

The downloadable files include all 16 feature rows.

Procedure

  1. Open the product from its canonical Sustainable Catalyst page or administrative route.
  2. Confirm the product and backend version before creating data.
  3. Create a synthetic workspace named CATALYST-ANALYTICS-R-RETROFIT-001.
  4. Download the CSV and JSON examples supplied below.
  5. Use the feature matrix to complete the first six feature checkpoints.
  6. Save, close, and reopen the workspace to verify persistence.
  7. Inspect warnings, sources, units, permissions, and lifecycle state.
  8. Export or hand off only after completing the verification checklist.

1. Data Intake

Action: read the feature-example CSV or JSON.

Expected result: a governed R data object.

2. Source Metadata

Action: attach publisher, URL, license, citation, retrieval, field, and unit metadata.

Expected result: a source-aware dataset.

3. Dataset Validation

Action: check required fields, types, missingness, units, and duplicates.

Expected result: a validation report.

4. Indicator Registry

Action: register annual energy savings.

Expected result: a reusable indicator definition.

5. Derived Indicators

Action: calculate baseline minus retrofit kWh.

Expected result: derived values with method metadata.

6. Comparison

Action: compare baseline and retrofit groups or periods.

Expected result: a comparison table and effect summary.

Expected output

  • a governed R data object
  • a source-aware dataset
  • a validation report
  • a reusable indicator definition
  • derived values with method metadata
  • a comparison table and effect summary
  • A saved record that reopens without data loss
  • An export or handoff that identifies product, version, artifact, source, and review state

Verification

  • Every sample value remains attached to its identifier and classification.
  • Warnings remain visible and are not silently treated as approval.
  • The saved workspace reopens in a clean session.
  • The product and version shown in output match the installed release.
  • Another reviewer can understand how the output was produced.

Responsible use

Statistical output requires method competence, source review, uncertainty communication, and domain interpretation; it is not automatic causal proof.

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