> ## Documentation Index
> Fetch the complete documentation index at: https://docs.dqlabs.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Asset Type

> Native classification assigned to a data object

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PRIZM organizes assets by its native type. Use the tab bar on the Assets page to filter the list to the type you need.

#### 1. Storage / Structural Assets

| Asset Type                 | Description                                                                                                                                      | Snowflake |
| :------------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------- | :-------- |
| **Database**               | A logical container holding schemas, tables, and other objects within a data warehouse or RDBMS (e.g., Snowflake database, PostgreSQL database). |           |
| **Schema**                 | A namespace within a database that groups related tables, views, and other objects together for organization and access control.                 |           |
| **Table**                  | A physical structured dataset stored in rows and columns; the most fundamental unit of stored data in a warehouse or database.                   | ✓         |
| **View**                   | A virtual table defined by a SQL query that dynamically pulls from underlying tables without storing data itself.                                | ✓         |
| **Materialized View**      | A view whose results are physically computed and stored, refreshed on a schedule or trigger, to improve query performance.                       |           |
| **Attribute**              | An individual data element within a table or view, including its data type, constraints, and statistical profile.                                |           |
| **Seed**                   | Static, version-controlled reference data (often CSV) loaded directly into the warehouse, common in dbt projects.                                |           |
| **Partition**              | A logical or physical subdivision of a table (often by date or key range) used to optimize query performance and storage.                        |           |
| **Index**                  | A database structure that improves the speed of data retrieval operations on a table at the cost of additional storage.                          |           |
| **Stage / External Table** | A reference to data sitting outside the warehouse (e.g., S3, GCS, Blob Storage) that can be queried without full ingestion.                      |           |

***

#### 2. Connection / Infrastructure Assets

| Asset Type     | Description                                                                                                                           |
| :------------- | :------------------------------------------------------------------------------------------------------------------------------------ |
| **Warehouse**  | A compute and storage platform instance (e.g., Snowflake, Redshift, BigQuery, Databricks) that hosts databases and processes queries. |
| **Source**     | A raw, upstream system or connector definition from which data is ingested (e.g., Salesforce, Postgres, Kafka, API).                  |
| **Account**    | A platform-level or service-level entity representing a tenant or organizational unit within a connected system.                      |
| **Site**       | The top-level container in BI platforms like Tableau, representing an isolated workspace or organization unit.                        |
| **Project**    | An organizational grouping of related assets, common in dbt, Looker, Power BI, and Tableau, used to scope permissions and structure.  |
| **Cluster**    | A compute resource grouping (e.g., a Databricks cluster or Spark cluster) used to run jobs and queries.                               |
| **Connection** | A configured link between a tool and a data source/destination, often used in ETL/ELT tools like Fivetran or Airbyte.                 |

***

#### 3. Transformation / Modeling Assets

| Asset Type                      | Description                                                                                                                                                           |
| :------------------------------ | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Model**                       | A transformed, version-controlled definition of data logic, most commonly associated with dbt models (staging, intermediate, mart layers).                            |
| **Query**                       | A saved or ad-hoc SQL statement used to retrieve, transform, or analyze data; tracked for lineage and reuse.                                                          |
| **Worksheet**                   | A saved SQL workspace (e.g., Snowflake Worksheets, Redshift Query Editor) used for interactive querying.                                                              |
| **Macro**                       | A reusable, parameterized SQL snippet or function, common in dbt, used to standardize transformation logic.                                                           |
| **Function / Stored Procedure** | A reusable block of SQL or code logic stored in the database, executed on demand or as part of a pipeline.                                                            |
| **Semantic Model**              | A business-friendly abstraction layer defining metrics, dimensions, and relationships, used in tools like Looker (LookML), dbt Semantic Layer, and Power BI datasets. |
| **Metric / KPI**                | A defined, calculated business measure (e.g., revenue, churn rate) often tied to a semantic model for consistent reporting.                                           |

***

#### 4. Pipeline / Orchestration Assets

| Asset Type                       | Description                                                                                                                                  |
| :------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------- |
| **Pipeline**                     | An end-to-end data flow definition that moves and transforms data from source to destination (ETL/ELT).                                      |
| **Job**                          | A scheduled or triggered unit of execution that runs one or more tasks (e.g., Airflow DAG run, dbt job, Databricks job).                     |
| **Task**                         | An individual step or unit of work within a job or pipeline (e.g., a single dbt model run, an Airflow task).                                 |
| **DAG (Directed Acyclic Graph)** | A workflow definition representing task dependencies and execution order, central to orchestration tools like Airflow, Dagster, and Prefect. |
| **Workflow**                     | A broader term for an orchestrated sequence of jobs/tasks, used interchangeably with pipeline or DAG depending on the platform.              |
| **Trigger**                      | An event or schedule definition that initiates a job or pipeline run (e.g., cron schedule, file arrival, API call).                          |
| **Run / Execution**              | A single instance of a job, pipeline, or task being executed, with associated logs, status, and duration.                                    |

***

#### 5. Quality Assets

| Asset Type | Description                                                                                                              |
| :--------- | :----------------------------------------------------------------------------------------------------------------------- |
| **Test**   | A data quality validation rule (e.g., not null, uniqueness, referential integrity) applied to a table, column, or model. |

***

#### 6. Consumption / Reporting Assets

| Asset Type                | Description                                                                                                                      |
| :------------------------ | :------------------------------------------------------------------------------------------------------------------------------- |
| **Dashboard**             | A visual collection of charts, metrics, and KPIs assembled for monitoring and decision-making (e.g., Tableau, Power BI, Looker). |
| **Report**                | A structured, often static or scheduled, presentation of data intended for distribution to stakeholders.                         |
| **Workbook**              | A container holding multiple dashboards, sheets, or worksheets, common in Tableau and Excel-based BI tools.                      |
| **Exposure**              | A defined downstream consumer of data (e.g., a dashboard or application) tracked explicitly in dbt for lineage purposes.         |
| **Chart / Visualization** | An individual visual element (graph, chart, table) within a dashboard or report.                                                 |
| **Dataset**               | A curated, often denormalized dataset prepared specifically for BI tool consumption (e.g., Power BI Dataset, Looker Explore).    |
| **Application / App**     | An interactive data application built on top of curated datasets, common in platforms like Looker (Looker Studio) and Sigma.     |