Worked Examples

Catalyst Analytics R: End-to-End Sample Workflow

Complete an all-feature retrofit demonstration in Catalyst Analytics R.

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
← Back to product guides

Catalyst Analytics R · How-to Guide

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 end-to-end workflow demonstrates every documented Catalyst Analytics R capability through one fictional resilient-community-retrofit case. The objective is not to prove a real-world conclusion; it is to verify the complete product workflow with controlled data.

Prerequisites

  • The current product release
  • A new synthetic workspace
  • The all-feature CSV and JSON
  • No production or private information
  • Time to review every checkpoint

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

Scenario

A community center is assessing energy, comfort, financing, implementation, evidence, and monitoring needs. Use only the supplied fictional records.

  1. 1. Data Intake: read the feature-example CSV or JSON. Confirm a governed R data object.
  2. 2. Source Metadata: attach publisher, URL, license, citation, retrieval, field, and unit metadata. Confirm a source-aware dataset.
  3. 3. Dataset Validation: check required fields, types, missingness, units, and duplicates. Confirm a validation report.
  4. 4. Indicator Registry: register annual energy savings. Confirm a reusable indicator definition.
  5. 5. Derived Indicators: calculate baseline minus retrofit kWh. Confirm derived values with method metadata.
  6. 6. Comparison: compare baseline and retrofit groups or periods. Confirm a comparison table and effect summary.
  7. 7. Uncertainty: apply an explicit ±8% measurement range. Confirm intervals and assumptions.
  8. 8. Sensitivity: vary tariff and occupancy inputs. Confirm a ranked sensitivity result.
  9. 9. Stress Testing: model 20% lower savings and 15% higher cost. Confirm stress-case outputs.
  10. 10. Accounting: reconcile monthly and annual energy totals. Confirm a balance check.
  11. 11. Workspaces: save data, indicators, assumptions, and outputs. Confirm a persistent analytical state.
  12. 12. Snapshots: freeze and restore complete workspace state. Confirm a fingerprinted snapshot.
  13. 13. Reproducible Reports: render methods, figures, results, and limitations. Confirm a rerunnable report.
  14. 14. Canonical JSON Export: export the reviewed comparison. Confirm a schema-versioned JSON record.
  15. 15. Browser Demo Parity: repeat the conceptual workflow in the public demo. Confirm a mapped result with parity limits.
  16. 16. Package Validation: run tests, examples, documentation checks, and R CMD check. Confirm a release-validation report.

Save and review

  1. Save the final workspace under the sample workspace ID.
  2. Close and reopen it in a clean session.
  3. Compare every feature result with the sample expected_result field.
  4. Document unresolved differences and do not hide warnings.
  5. Export one complete artifact bundle.
  6. Send one supported handoff to an integration and verify its receipt.

Supported integrations

  • Catalyst Data
  • Decision Studio
  • Research Lab
  • Workbench
  • Knowledge Library

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
  • intervals and assumptions
  • a ranked sensitivity result
  • stress-case outputs
  • a balance check
  • a persistent analytical state
  • a fingerprinted snapshot
  • a rerunnable report
  • a schema-versioned JSON record
  • a mapped result with parity limits
  • a release-validation report
  • A complete saved workspace
  • A portable export
  • A validated cross-product handoff receipt

Verification

  • Every CSV feature row has a corresponding saved result.
  • The JSON workspace ID and product version are preserved.
  • The export can be inspected without temporary browser state.
  • The receiving product identifies source, destination, schema, artifact, and review state.
  • A human reviewer can reproduce or audit the demonstration.

Responsible use

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

Replace synthetic data only with information you are authorized to use, after reassessing licensing, privacy, uncertainty, and review obligations.

Scroll to Top