---
title: "Use Case Guide: Data Exploration"
url: "https://atlan.com/resources/use-case-data-exploration/"
description: "A guide to Atlan's data exploration - using Insights, saved queries, and Visual Query Builder to empower both technical and non-technical users."
keywords: "atlan, use case guide data exploration"
---

> Atlan is hosting Context Conference, bringing together the leaders and builders at the frontier of giving AI the context it needs to understand their business. It runs online on October 28, 2026, from 11:00 AM to 2:00 PM ET. Atlan co-founder Prukalpa Sankar opens and closes the day. Leaders from AstraZeneca, BNY and Verizon share why they invest in context and what they get from it. Registrants get early access to The AI Context Gap, a new study from MIT Technology Review Insights. Register: https://atlan.com/context-conference/

**Use Case Guide: Data Exploration.** An Atlan resource page; its description follows under the page's own heading.

## About this guide

A detailed guide to data exploration in Atlan: how technical and non-technical users query and analyze data with less dependency on specialists. Challenges addressed: uncertainty about which assets to use, restricted access for non-technical users, and high reliance on SQL experts.

### Three levels of solutions

1. **Write and run SQL in Atlan Insights** (page 4). Atlan's native query editor integrates metadata: hover over or open asset profiles for instant context. Supports dbt semantic layer integration and scheduled queries.
2. **Save and share queries** (page 5). Technical users save queries as reusable assets, organize them into collections, and share them with non-technical colleagues. Saved queries carry metadata such as owners and certificates, so business users can rely on them.
3. **Self-serve with the Visual Query Builder** (page 6). Non-technical users build SQL-like queries through dropdowns and filters for grouping, aggregating, joining, and sorting, with no coding required.

### Measuring business impact (page 7)

Measure time saved on data access tickets and query writing. Capture system metrics (number and duration of tickets) and survey responses to assess reduced dependency and improved efficiency.

## Related resources

- [Use Case Guide: Impact Analysis](https://atlan.com/resources/use-case-impact-analysis) (guide)
- [Data Governance Examples: Real-World Case Studies for 2025](https://atlan.com/data-governance-examples/) (explainer)