Analyze hub
Inspect structure, size, and quality signals before transformation or export.
Hub intro and use cases
Use this hub to understand your data profile and spot issues before downstream steps.
- Measure JSON payload size and nesting complexity.
- Review CSV statistics before cleaning pipelines.
- Assess data shape to choose the right conversion workflow.
On this page
Jump to each section quickly.
Workflows in this hub
Touching = workflows with at least one analyze tool. Primary = first step is analyze or most steps are analyze.
Validate CSV then CSV Statistics
Validate raw CSV first, then run CSV Statistics for a safe, repeatable pipeline.
Use case
Use this when incoming CSV quality is uncertain and you want a validation gate before running CSV Statistics.
Clean CSV then CSV Statistics
Normalize CSV structure before running CSV Statistics to reduce downstream surprises.
Use case
Use this when exports have inconsistent spacing/quoting and you want better results from CSV Statistics.
Sort CSV and Prepare Analysis View
Sort records and then profile structure with statistics for a quick analysis-ready snapshot.
Use case
Use this before exploratory analysis to quickly verify sort order and understand column quality/shape.
Validate and Analyze JSON Size
Validate JSON and generate payload size metrics to support performance and transport planning.
Use case
Use this for API payload checks where validity and byte-size impact both matter.
Size Audit then Minify JSON
Measure JSON payload size first, then minify it to compare delivery footprint.
Use case
Use this when optimizing payload transfer costs and latency.
JSON Size Analyzer Output Sanity Check
Run JSON Size Analyzer and immediately inspect the resulting payload format to verify the output is ready for the next handoff.
Use case
Use this when you want a quick confidence check that json size analyzer produces the kind of payload you expect before wiring it into larger workflows or sharing results.
CSV Statistics: Quality Gate
Run CSV Statistics in a guardrailed pipeline that validates and prepares data for downstream consumption.
Use case
Use this when csv statistics is part of a repeatable process and you want a quality check before/after the core transformation.
CSV Statistics: Delivery Flow
Use CSV Statistics as a middle step, then shape output for delivery to APIs, reports, or handoff files.
Use case
Use this when you need csv statistics plus a final delivery-oriented output format.
JSON Size Analyzer: Quality Gate
Run JSON Size Analyzer in a guardrailed pipeline that validates and prepares data for downstream consumption.
Use case
Use this when json size analyzer is part of a repeatable process and you want a quality check before/after the core transformation.
JSON Size Analyzer: Delivery Flow
Use JSON Size Analyzer as a middle step, then shape output for delivery to APIs, reports, or handoff files.
Use case
Use this when you need json size analyzer plus a final delivery-oriented output format.
Profile and Clean CSV
Profile CSV columns first, then clean and validate the dataset.
Use case
Use this to identify sparse or mixed columns before normalizing CSV exports.
CSV Full Data QA
Run a full CSV quality pass with cleaning, profiling, and summary statistics.
Use case
Use this to baseline incoming CSV files before conversion or loading tasks.
Profile CSV Then Convert to JSON
Profile column quality and convert CSV to JSON for downstream workflows.
Use case
Use this when you want both quick data profiling and a JSON handoff output.
JSON Analysis Pipeline
Validate JSON, profile field types, then generate a schema snapshot.
Use case
Use this to check API payload consistency before schema capture.
API Response Quality Check
Format a raw API response and profile field type consistency.
Use case
Use this when an API payload changes and you need fast type drift detection.
Profile Filtered JSON
Filter JSON records and profile the resulting subset for type consistency.
Use case
Use this to inspect type quality in targeted slices of larger payloads.
XML Exploration Pipeline
Analyze XML structure, inspect tree hierarchy, then evaluate XPath.
Use case
Use this when onboarding unknown XML payloads before writing extraction queries.
XML Analyze Before Convert
Analyze XML complexity before converting to JSON.
Use case
Use this to understand source XML shape before transformation to object models.
XML Schema Capture
Analyze XML and generate a schema representation for governance.
Use case
Use this for schema-first documentation of legacy XML feeds.
YAML Config Audit
Validate YAML, analyze structure, and run schema validation for stronger config controls.
Use case
Use this to audit production YAML files before rollout.
YAML Analyze and Explore
Analyze YAML metrics then inspect nested structure in tree view.
Use case
Use this to quickly review deep config files and key distribution.
YAML Analyze and Lint
Analyze YAML structure and then lint for style and maintainability issues.
Use case
Use this before committing large YAML updates to catch both structure and style concerns.
Schema Round Trip Audit
Generate a schema, analyze it, then validate data against schema rules.
Use case
Use this to verify schema quality and practical validation fit in one pass.
Schema Quality Check
Analyze schema quality and then validate representative payloads.
Use case
Use this as a fast governance check before publishing schema updates.
Generate and Audit Schema
Validate JSON input, infer schema, and audit schema quality metrics.
Use case
Use this to bootstrap and assess a schema from real payload samples.
Pivot CSV Then Analyze
Create a pivot table from CSV, then profile the output columns.
Use case
Use this to generate summary tables and immediately inspect column characteristics.
Generate and Profile CSV
Generate mock CSV and immediately profile column quality metrics.
Use case
Use this for synthetic analytics fixture generation with quick data-quality review.
Schema Round Trip
Generate schema, analyze it, build a template payload, then validate it.
Use case
Use this to test schema quality and ensure generated payload templates validate cleanly.
YAML Config Audit
Validate and analyze YAML, then infer and validate schema.
Use case
Use this for deep audits of infrastructure config before deployment.
CSV Data Exploration
Clean CSV, compute statistics, and visualize trends with a chart.
Use case
Use this for quick visual exploration of tabular data before deeper analysis.
Profile and Chart CSV
Profile columns and then chart selected metrics for quick trend checks.
Use case
Use this to identify quality signals and visualize key columns in one flow.
Statistics and Heatmap
Run CSV statistics and then inspect row-level gradients in a heatmap.
Use case
Use this to pair summary metrics with visual cell-level distribution signals.
Profile and Detect CSV Anomalies
Profile CSV columns, detect anomalies, then clean flagged data.
Use case
Use this for quality checks before ingestion when data consistency is uncertain.
Full CSV Data QA
Run end-to-end CSV quality checks with anomaly detection and filtering.
Use case
Use this to enforce stricter QA gates on CSV datasets before handoff.
Anomaly Check Before Load
Detect anomalies, validate CSV shape, then convert to JSON for loading.
Use case
Use this before ETL/database import to catch issues early.