Databricks DA-ASSOC glossary of SQL, dashboards, Genie, modeling, and data security terms.
Use this glossary when Databricks SQL and analytics terms start to blur together. Keep it beside the cheat sheet and resources, not as a substitute for them.
| Term | Short meaning | Why it matters on DA-ASSOC |
|---|---|---|
| Databricks Data Intelligence Platform | Databricks platform layer for data, analytics, AI, governance, and SQL workloads | Top-level platform scope on the exam |
| Unity Catalog | Databricks governance layer for data objects, permissions, and lineage | Core trusted-analytics boundary |
| SQL Warehouse | Compute service used to run Databricks SQL queries | Core execution and workflow term |
| Query history | Record of executed SQL queries and their execution details | Important for debugging and analysis |
| Query Profile | Detailed execution view for a query | Important for performance-analysis questions |
| Query Insights | Databricks feature for spotting poorly performing queries | Common performance-analysis aid |
| Photon | Databricks execution engine for fast analytics workloads | Common query-performance concept |
| Liquid clustering | Table-layout optimization approach for filtered analytics workloads | Optimization concept in query analysis |
| Materialized view | Stored precomputed query result refreshed by the platform | Commonly contrasted with streaming tables and standard views |
| Streaming table | Table designed for continuously arriving data workflows | Important in freshness and workload-shape questions |
| Genie space | AI/BI workspace that helps users interact with curated data through natural language | Distinct consumption and trust boundary |
| Trusted asset | Curated query or object treated as reliable inside Genie workflows | Important Genie governance concept |
| Certified dataset | Data asset marked as trusted and governed for use | Trusted-data concept |
| Delta Sharing | Sharing data with external systems without raw-copy handoff | Common external-consumption concept |
| Lakehouse Federation | Querying external systems from Databricks without first ingesting all data | Important import-versus-query decision concept |
| Auto Loader | Incremental ingestion feature for files arriving in cloud storage | Important import-path concept |
| Row grain | What one row is intended to represent in a query result | One of the most important correctness concepts |
| Widget parameter | Dashboard or query input control used to filter or alter behavior | Common dashboard question term |
| Alert threshold | Condition that triggers a notification | Important dashboard and alerting concept |
| Catalog Explorer | UI for discovering and managing governed data assets | Important Unity Catalog workflow term |
| External table | Table that points to data outside Databricks-managed storage | Commonly contrasted with managed tables |
| Managed table | Table with more platform-managed storage lifecycle | Governance and storage-boundary term |
| Pair | Keep this distinction clear |
|---|---|
| inner join vs left join | matched rows only versus preserve all rows from the left side |
UNION vs UNION ALL |
deduplicate combined rows versus keep all rows |
| materialized view vs streaming table | precomputed query result versus continuous data processing table |
| managed table vs external table | platform-managed storage versus externally referenced storage |
| dashboard refresh vs alert trigger | refresh the visual data versus notify on a condition |
| query history vs query profile | execution record versus detailed execution breakdown |
| query profile vs query insights | one-query execution detail versus broader performance insight tooling |
| certified dataset vs trusted asset | governed trusted data object versus trusted query or object inside Genie |
| widget parameter vs dashboard filter logic | input control value versus how the query actually uses it |
| Delta Sharing vs Lakehouse Federation | governed external sharing versus querying external systems in place |
| Cluster | Fast separation |
|---|---|
| row grain / join logic / aggregation | what one row means, how rows combine, and how rows collapse into metrics |
| SQL Warehouse / Query History / Query Profile | run the query, inspect what ran, and inspect why it behaved that way |
| materialized view / streaming table / standard query output | precomputed refreshed result, continuous data table, or direct query result |
| dashboard / alert / Genie space | visual consumption, threshold notification, or AI-assisted interaction layer |
| Unity Catalog / certified dataset / Delta Sharing | governance layer, trusted data object, or external sharing mechanism |
| Auto Loader / Lakehouse Federation / workspace upload | incremental ingestion, query-in-place access, or small manual upload path |
| Cluster | What it usually signals on the exam |
|---|---|
| row grain / joins / windows | SQL correctness questions |
| warehouse / history / profile / Photon | query-execution and analysis questions |
| dashboards / alerts / parameters | analytics-consumption questions |
| Genie / trusted assets / certified datasets | AI/BI and trust-boundary questions |
| Unity Catalog / managed tables / external tables / Delta Sharing | governance and sharing questions |
| Auto Loader / Marketplace / Federation | data-import and data-access questions |
| Topic family | Best page to revisit |
|---|---|
| SQL correctness and quick rules | Cheat Sheet |
| official Databricks facts and docs | Resources |
| pacing and review order | Study Plan |
| overall exam framing | Guide root |