Snowflake Complete Course + SnowPro Core Certification

Explore the three-layer Snowflake architecture—storage, processing with virtual warehouses, and cloud services—learn how micro partitions, columnar storage, and metadata management boost security and performance.

Understand virtual warehouses in Snowflake, the compute clusters that process queries, and how sizes scale from extra small to extra large with scale up and scale out via multi-cluster warehouses.

Learn how to create a Snowflake trial account and navigate the Snowflake site user interface, exploring accounts, warehouses, databases, cost management, monitoring, query history, and dashboards.

Explore how to create a Snowflake trial account and navigate the web-based Snowflake site, including data, worksheets, dashboards, and admin views, with 30 days and $400 credits for practice.

Explore how Snowflake automatically partitions data into micro partitions and uses metadata for query pruning, then learn how clustering and cluster keys improve performance by co-locating data.

Master data loading in Snowflake using bulk and continuous loading from external and internal stages, and transform data during load with file formats and transformations like substring and concatenation.

Create external stages in Snowflake to load data from cloud storage providers such as Amazon S3, Google Cloud Storage, or Microsoft Azure, using storage integration objects and file format definitions.

Log into SnowSQL by building the account identifier from your locator and region, then run 'snow sql -a <account_identifier> -u <username>' to log in and select database and schema.

Explains internal stages, including user stage, table stage, and named internal stage, and demonstrates uploading local files with put and loading into Snowflake tables via copy into, plus SnowSQL setup.

Explore copy command options such as validation mode, return errors, continue, skip file, size limit, truncate columns, purge for Snowflake data loads.

Learn to use snowflake's infer schema table function to derive metadata from CSV and JSON files in internal or external stages, with options for case sensitivity and file limits.

Set up a free AWS S3 account, create buckets and folders, and integrate Snowflake with S3 via IAM and storage integration to load data with external stages and copy commands.

Learn to integrate Snowflake with Azure by creating storage accounts and containers, configuring a storage integration and stage, and loading data with copy commands from Azure containers.

Process json data in Snowflake by loading semi-structured json into a variant stage, use external stages and file formats, then parse and flatten arrays and nested fields into relational tables.

Learn to process XML files in Snowflake by loading into a variant table via S3 storage integration, then flatten with XML get to populate a books table.