About this demo
This resource is a detailed guide to data exploration in Atlan, showing how both technical and non-technical users can query and analyze data with greater ease and less dependency on specialists. It addresses common challenges such as uncertainty around which assets to use, restricted access for non-technical users, and high reliance on SQL experts.
The guide outlines three levels of solutions. At Level 1, technical users can write and run SQL queries directly in Atlan Insights, Atlan’s native query editor. Unlike traditional editors, Insights integrates rich metadata, allowing users to hover over or open asset profiles for instant context, and even supports dbt semantic layer integration and scheduling queries (page 4).
At Level 2, technical users can save queries as reusable assets, organize them into collections, and share them with non-technical colleagues. These saved queries come with metadata fields like owners and certificates, helping build trust and ensuring business users can rely on them for decision-making (page 5).
At Level 3, non-technical users can self-serve with Atlan’s Visual Query Builder, which enables SQL-like queries through an intuitive interface of dropdowns and filters for grouping, aggregating, joining, and sorting data—no coding required (page 6). This makes data exploration more accessible, reducing bottlenecks and enabling democratized access.
The playbook also introduces a framework for quantifying business impact, recommending ways to measure outcomes like time saved on data access tickets and query writing. It suggests capturing both system metrics (e.g., number and duration of tickets) and survey responses to assess reductions in dependency and improvements in efficiency (page 7).
By combining technical capabilities with business impact measurement, this guide equips teams to make exploration faster, more collaborative, and more inclusive—ultimately driving stronger data-driven decisions.