Explore Snowflake features and architecture, including storage, compute, and services layers, objects and their container hierarchy, billing, and connections like Snowpark and Snowflake Scripting.

Discover Snowflake as a cloud-native data platform offered as a service, uniting data warehouse and data lakehouse capabilities with features like Snowpipe, Openflow, and Cortex for diverse workloads.

Snowflake's storage layer uses the cloud blob store (example amazon s3) with high availability and durability, storing data in a centralized, encrypted columnar format with micro-partitions for efficient sql queries.

Explore the query processing (compute) layer in Snowflake, featuring virtual warehouses that scale out compute, pause and resume, isolate workloads, and ensure strict ACID processing via the transaction manager.

Explore the Snowflake services layer, including authentication and access control, infrastructure management, transaction and metadata management, query parsing and optimization, and security, to understand global coordination across accounts.

Explore how Snowflake parameters—account, session, and object—shape behavior with alter commands, precedence rules, and practical examples like periodic_data_rekeying.

Configure account, session, and object parameters in Snowflake—set date formats and defaults, enable Workspaces as the default sql editor, and explore data retention time across database, schema, and table.

Explore UDFs, external functions, and stored procedures in Snowflake with hands-on exercises that create, call, and manage SQL and JavaScript code, including API integrations and cross-language use.

Fine-tune a smaller model on sentiment labels from a large model to reduce costs and improve accuracy; leverage Cortex Search with embeddings for semantic queries in Snowflake.

Explore Snowflake access control frameworks—RBAC, discretionary, and user-based—role ownership, privilege grants, and object hierarchies to enforce least privilege across securable objects.

Explore Snowflake access control by creating and managing roles, grants, and privilege inheritance, including custom roles, future grants, and object ownership.

Generate a 2048-bit private key pair and assign the public key to a Snowflake user. Enable key pair authentication via connectors and rotate with two active keys to avoid downtime.

Set up and test column and row level security with masking and mapping table policies, using system admin, analyst, and masking admin roles to control data access.

Explore how the Snowflake account usage views and the information schema provide historical usage, credits, and metadata across accounts, with latency and access considerations for reporting.

Snowflake alerts are schema-level watches that evaluate a condition, execute an action, and trigger on a schedule or new rows, with serverless or warehouse compute options.

Analyze Snowflake query performance using query history, query profile, and account usage views to identify long-running queries, bottlenecks, and optimization opportunities.

Learn practical SQL tuning for Snowflake: optimize queries with early where filters, proper joins on unique columns, mindful grouping and ordering, and avoiding spills by managing memory and cardinality.

Snowflake caching uses the metadata cache, the results cache, and the local disk cache (SSD) to speed queries, with a 24-hour results cache and an LRU warehouse cache.

Explore materialized views, which store pre-computed query results and refresh automatically to balance freshness and performance. Learn limitations, costs, and use cases, including external tables.

Demonstrates how well-clustered keys boost pruning and speed up queries on large Snowflake tables, by examining clustering metadata, overlap, and depth with hands-on exercises.

Explore simple data loading techniques in Snowflake, including insert statements and loading via the UI from CSV, with mapping, file formats, and a hands-on walkthrough.

Learn how to use the copy into <table> bulk loading command to move data from internal or external stages into Snowflake tables, with format options, transformations, and validation.

Snowflake uses file_format options on stages or COPY INTO statements to identify file types like CSV, JSON, and XML, and to handle headers, compression, and encoding during loading.

Explore how Snowflake uses estimation functions to approximate cardinality, similarity, frequency, and percentile with HyperLogLog, MINHASH, Approx_Top_K, and T digest for faster insights.

Explore Snowflake’s storage layer: centralized scalable blob storage (s3/azure blob/cloud storage), auto micro-partitions, data reorganization into compressed and encrypted columnar format, supporting structured and semi-structured data accessed via SQL.

Learn how Snowflake calculates storage billing based on daily on-disk data for tables and internal stages, including time travel, fail-safe, and retention impacts, with regional per-terabyte pricing and example costs.

Explore Snowflake's data marketplace in Snowsight, where data providers publish standard or personalized listings for data consumers, enabling rapid access, customized requests, and potential charges.

Learn how to create a private data exchange in Snowsight, and invite providers and consumers to share data. Manage access, approve listings, and monitor listing requests.