Reference to the Project Reference to which it applies, for example the objects Hierarchical framework, you would then name all the objects with strict Then below that, various functions pertaining to the levelĪbove such as 1a, 1b, 1c, 2a, 2b, 2c, 3a, 3b, 3c etc. So, the top level menu might have something like 1. If this were the case, then I would use what IĬall for want of a better term, Project References. Organized hierarchically with buttons on a main opening form leading to So far, I’ve worked with over 50 Snowflake customers, and find using these simple practices greatly ease the development burden and let you get on with the more challenging subjects, like understanding your data, your requirements and how to get the very best out of Snowflake.ĭisclaimer: The opinions expressed on this site are entirely my own, and will not necessarily reflect those of my employer.Let's just say for the sake of argument that your database application is This means a given zone can hold multiple schemas, with each prefixed by the same code.įinally, we saw the need to refer to all objects at the schema level, ideally setting a default database for each user, and then switching the database, warehouse and role to move between different environments within the system. The article went on to describe best practices for Snowflake naming conventions, and the importance of naming the Roles, Virtual Warehouses and Database with a prefix to indicate the environment, and how this naming convention can be used to prefix areas or zones within the database which should be implemented as schemas prefixed by a short code to indicate the type. This makes it much easier to produce and maintain test data from a production database. It’s worth noting, the primary driver behind hosting multiple environments on a single account is the ability to clone tables, schemas or even entire databases. It described the main options to deploy accounts including a common mistake of creating one account for each Development, Test and Production environment and summarised the alternative options which include deploying a single account with environments separated using Role Based Access Control and dual accounts. This article briefly describes the way Snowflake structures objects within an Account into a Database and Schemas. At the same time, the raw history is held in the Raw Staging area, and data prepared in the Integration or Workbench schemas and reported from the Marts area. The diagram below illustrates a potential standard data architecture whereby data is loaded from Cloud Storage into a Landing area. WRK – To indicate workbench schemas, which provide a sandbox for data analysts. MRT – To indicate a data mart holding conformed and cleaned data ready for reporting. INT – To indicate an integration area where raw data is combined and cleaned before analysis. LND – To indicate a landing schema used to hold newly ingested data. Naming conventions for schemas must not include the environment name (for reasons which will become evident later), but it may be sensible to prefix schema names to indicate the purpose. This is important because regardless of the Snowflake Account deployment strategy, you will find you need to hold multiple environments within the same account, and therefore each Role, Warehouse, and Database name must include a code indicating the environment. Within each Snowflake Account, the user can deploy an unlimited number of Databases, and within each database, an almost unlimited number of schemas to hold tables, views, and materialized views. Snowflake is accessed via one or more independent Accounts with each identified by a unique URL. Account, Database and Schemas and Environmentsīefore describing the best practice, it’s helpful to understand the database hierarchy within a Snowflake deployment. Get it right, and your project has the opportunity to fly. Get it wrong, and you’ll struggle to get the best out of Snowflake. It explains what options you have for accounts (single, dual, or multiple), a naming convention for databases and schemas, and proposes a sensible data architecture to deploy your data warehouse.Īlthough the Snowflake database is incredibly easy to use, there are some excellent best practices around the deployment of Snowflake Account, Databases, Schemas. This article explains the best practices for Snowflake databases, schemas, and naming conventions.
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