--- title: CORE data model slug: o1ad6219 canonical_url: https://docs.coveo.com/en/o1ad6219/ collection: coveo-analytics source_format: adoc --- # CORE data model The CORE data model in Snowflake serves as the foundational architecture that defines the structure and relationships of [Coveo Analytics](https://docs.coveo.com/en/182/) [data](https://docs.coveo.com/en/259/). Raw [events](https://docs.coveo.com/en/260/) can be challenging to interpret. The data model organizes them into a normalized format with a clear domain model which makes it easier to understand and query the data. Within the CORE model, there are three schemas: [COMMON](#common-schema), [COMMERCE](#commerce-schema), and [ANSWERING](#answering-schema). All schemas contain data tables, which store event data in a structured format. Views are built on top of those tables and present the data in a suitable format for analysis and reporting. In other words, the CORE model is how your Coveo Analytics data is organized in Snowflake. Schemas group related data tables together, and views provide ready-to-query datasets. This hierarchical organization ensures that the data isn't just well-structured, but also accessible for strategic decision-making. > **Note** > > The schemas are available to all clients. > However, the COMMERCE schema contains data only for Coveo for Commerce clients and the ANSWERING schema for clients who leverage the RGA model. > For all other clients, the COMMERCE and ANSWERING schemas have empty views. You can access the CORE data model in Snowflake through a [reader account](https://docs.coveo.com/en/l9e90297/) which provides read-only access to the data. Alternatively, you can use the [Data Share feature](https://docs.coveo.com/en/m1rf0146/) to connect your own Snowflake account with your Coveo Analytics data, allowing you to query the data directly from your own Snowflake environment. ## COMMON schema The COMMON schema encompasses a broad range of views that provide core [metrics](https://docs.coveo.com/en/263/) across Coveo implementations. It provides foundational [events](https://docs.coveo.com/en/260/) such as searches, clicks, impressions, visits, and visit-related [events](https://docs.coveo.com/en/260/) (see [COMMON schema reference](https://docs.coveo.com/en/o1jc0451/)). ![Coveo | COMMON schema in Snowflake](https://docs.coveo.com/en/assets/images/coveo-analytics/common-schema.png) ## COMMERCE schema The COMMERCE schema is specifically tailored to Coveo for Commerce implementations, with views that deliver insights into commerce-related activities. It focuses on transaction and cart-related data (see [COMMERCE schema reference](https://docs.coveo.com/en/p19a0120/)). ![Coveo | COMMERCE schema in Snowflake](https://docs.coveo.com/en/assets/images/coveo-analytics/commerce-schema.png) ## ANSWERING schema The ANSWERING schema captures [Relevance Generative Answering (RGA)](https://docs.coveo.com/en/nbtb6010/) data, with a focus on generated answers and interactions (see [ANSWERING schema reference](https://docs.coveo.com/en/pbab7533/)). ![Coveo | ANSWERING schema in Snowflake](https://docs.coveo.com/en/assets/images/coveo-analytics/answering-schema.png) ## Advantages of using the CORE model schemas The schemas available in Snowflake are similar to accessing a comprehensive data warehouse for your analytics needs. The schemas cover a wide range of [metrics](https://docs.coveo.com/en/263/) and [dimensions](https://docs.coveo.com/en/258/) pertinent to different Coveo services, offering you a detailed roadmap of the data landscape. They help you understand and use the data effectively, ensuring that you can interpret and query the data accurately. Whether it's for generating custom reports or optimizing data-driven strategies, these schemas provide the required foundational structure to do so. More specifically, they allow you to: * Understand report structure By examining the schemas, you can identify which tables and fields are used in Coveo's out-of-the-box (OOTB) [reports](https://docs.coveo.com/en/266/). For instance, if a report is about user engagement, you might look at tables and views related to user activities, such as `CLICKED_IMPRESSIONS` or `EVENTS` in the COMMON schema. * Replicate queries With knowledge of the underlying tables and fields, you can write SQL queries to replicate the data retrieval process of the OOTB reports. This involves using `JOIN`, `WHERE` clauses, and other SQL operations to fetch and organize data in a similar structure to the original report. * Customize and enhance reports Once you understand how the OOTB reports are structured, you can modify or extend these reports to better suit your needs. For example, you might add additional [filters](https://docs.coveo.com/en/2736/), combine data from multiple views, or incorporate data from external sources. ## What's next? * To learn more about the COMMON schema, see [COMMON schema reference](https://docs.coveo.com/en/o1jc0451/). * To learn more about the COMMERCE schema, see [COMMERCE schema reference](https://docs.coveo.com/en/p19a0120/). * To learn more about the ANSWERING schema, see [ANSWERING schema reference](https://docs.coveo.com/en/pbab7533/).