Snowflake for Beginners: Intro to Cloud Data Warehousing

Explore snowflake architecture across its three layers: database storage, query processing, and cloud service, and how elastic storage and elastic compute enable cloud-agnostic data access across aws, gcp, and azure.

Snowflake offers four editions—standard, enterprise, business critical, and a separate compute-and-storage edition. Enterprise adds multi-clustered virtual warehouses, materialized views, and extended time travel; business critical adds failover and data recovery.

Sign up for a 30-day snowflake trial with up to $400 of free usage, choose aws us west region, activate via email, and log in to explore the snowflake ui.

Navigate the snow site UI to explore projects, data, and objects; create worksheets, notebooks, dashboards, and apps; manage data sources, AI and ML tools, and governance settings.

Compare worksheet and notebook in the snow site. Worksheet lets developers write SQL or Python to create objects and view data; notebooks support data scientists building models and testing artifacts.

Explore how to use the SQL worksheet in Snowflake to create a database, schema, and table, insert records, and query or describe objects with metadata insights.

Navigate Snowflake ui changes, comparing old ui and new workspace with worksheets and sql files, while learning how to switch databases, roles, and compute warehouse.

Create and run a Python worksheet with Snowpark to query Snowflake data, filter information_schema.packages by language, and preview results for exam preparation.

Explore the hierarchy of Snowflake containers, from organization and accounts to databases, schemas, and objects like tables, views, stages, stored procedures, and user defined functions.

Learn how to use SnowSight to create databases, schemas, and tables from files, configure data types and headers, and monitor queries through history and grouped queries.

Learn to create and manage a snowflake notebook, choose a warehouse and runtime, and run Python, SQL, and Markdown in a jupiter-style notebook.

Snowflake provides non-materialized, materialized, and secure views; a view wraps a query without storing data, while a materialized view stores data for faster queries, with secure views enhancing access control.

Create normal, materialized, and secure views in Snowflake using create or replace view, materialized view, and secure commands, then verify with show views and sample selects.

Explore how Snowflake's access control framework combines discretionary access control and role-based access control to grant privileges on securable objects to roles and users, with role hierarchies.

Explore Snowflake roles, including account and database roles, and how privileges are granted to objects, with primary and secondary roles shaping access.

Demonstrates building an access control framework in Snowflake by creating users and roles, granting privileges on databases, schemas, and tables, and establishing a role hierarchy.

Demonstrates a Snowflake role hierarchy with dummy roles, granting usage on database, schema, and warehouse, and cascading privileges from lower to higher roles while assigning roles to a user.

Learn core snowflake sql commands, including creating tables, inserting records, selecting data with limits, excluding columns, and aggregating sums and grouping by department, using the default public schema.

Demonstrate Snowflake features by creating a table in schema two, dropping a schema, and using full path to access objects while checking current warehouse, database, schema, and user.

Demonstrates granting ownership of a schema to a role and using information schema to inspect database metadata and objects.

Snowflake loads structured, semi-structured, or unstructured data from cloud or on-prem sources into a stage, location of data files in cloud storage, with internal, external, named, table, and user stages.

Explore how to create and use an internal Snowflake managed stage to load data into a table, including file formats, headers, error handling, and duplicates.

Learn how to use user stage and table stage to load mock csv data into a Snowflake table, using put and copy into with purge option.

Explore semi-structured data in snowflake, where tagging and nesting create records, exemplified by a JSON customer file, and learn native types like array, object, and variant for loading and querying.

Load json semi-structured data into a Snowflake table by creating a json file format and stage, then query nested fields with bracket or dot notation and insert using parse_json.

Generate and access unstructured data URLs using stage and file URL methods, including pre-signed URLs with expiration, and observe how non-deterministic URLs change on each access.

Explore how directory stores file-level metadata and file URLs in a Snowflake stage, enabled at create or alter, with manual refresh for internal stages and automatic refresh for external stages.

Learn how to create and manage Snowflake warehouses, including standard and Snowpark optimized types, extra small through four x large sizes, auto resume and suspend, multi-cluster scaling, and query acceleration.

Compare standard and multi-cluster warehouses, detailing compute resources, sizes from extra small to six x large, 1 to 10 clusters, soft limit of ten, and dynamic scaling.

Scale Snowflake with scale out for multi-cluster warehouses and scale up or down to handle load, using standard or economy scaling policies, noting multi-cluster requires enterprise edition.

Explore permanent, transient, and temporary tables and their default creation syntax in Snowflake, and learn to view definitions, insert data, copy into, and load data for exam prep.

Explore snowflake cortex lm functions and ai sql functions, with helper functions to access enterprise llms like openai and meta models for unstructured data.

The Cortex LLM function demo teaches AI parse document with OCR and layout modes, translate, classify, and complete tasks using Snowflake models.

Explore Snowflake time travel to view data at a timestamp. Configure retention from 0 to 1 day and up to 90 days in enterprise edition, with seven-day fail safe.

Learn how time travel works in Snowflake by selecting database, schema, and warehouse, setting UTC, and using timestamp, offset, and statement to view data history, cloning, and retention days.

Explore snowflake cloning, creating exact copies of databases, schemas, and tables that share data while paying storage only for the original records. Grasp cloneable objects, time travel, and privilege basics.

Learn how to clone tables in Snowflake and keep clones independent from the original. Then use time travel to restore deleted data with clone tables.

Access data, apps, and AI products via Snowflake marketplace, discover offerings, and quickly obtain them in your Snowflake environment with free to try options.

Learn how to use Snowflake data exchange to share data with internal and external partners, publish listings, manage access, and control direct shares or readers accounts.