SNAP Getting Started

SNAP (Smart oNe-stop digitAl data shoP) is an open-access data lake that combines primary and secondary datasets on jobs, skills, and socio-economic conditions across European regions.

This guide helps a new user go from first login to first analysis in less than 30 minutes.

What you can do in SNAP

• Discover available datasets by theme, source, country, region, year, and update cycle.
• Inspect metadata, quality indicators, and lineage for every dataset.
• Build simple exploratory analyses and export snapshots for reporting.
• Reuse saved filters and compare regions over time.

User roles (debug simulation)

SNAP can be tested with these fake roles:

• Guest Analyst: read-only access to public datasets.
• Research Partner: read + workspace-level saved views.
• Data Steward: ingestion and metadata editing permissions.

Quick start workflow

1. Open SNAP from the top navigation.
2. Select the default workspace (for testing: EU Labour Transition Sandbox).
3. In the catalog, search for employment, skills, or NUTS2.
4. Open one dataset and verify metadata appears.
5. Add two filters (e.g., country and year).
6. Save a temporary view called debug-first-view.

First analysis recipe

Use this minimal recipe to test end-to-end behavior:

• Dataset: Regional employment rate.
• Dimension A: Region (NUTS2).
• Dimension B: Year.
• Metric: Employment rate (%).
• Expected output: Trend chart + table with region/year values.

Debug checklist

• Dataset card loads title, description, and source.
• Metadata tab opens without console errors.
• Filters update chart and table simultaneously.
• Saved view appears in user shortcuts.

Common first-day mistakes

• Filtering both EU27 and individual countries at the same time.
• Mixing absolute counts with percentage indicators in one chart.
• Comparing non-aligned year ranges across datasets.

Recommended naming conventions

For reusable debug assets:

• Saved views: debug-[tool]-[purpose]-[date]
• Exports: snap-export-[theme]-[region]-[yyyy-mm-dd]
• Notes: snap-note-[dataset-code]-[short-topic]

Next pages

After this guide, continue with:

• Data catalog usage
• Ingestion pipeline simulation
• Query and filter behavior