Snowflake Course

Master cloud data management with our expert-led Snowflake training.

Master Snowflake

Unlock the full potential of Snowflake, the leading cloud data platform, with our comprehensive training course designed for data professionals.

This Course Includes

  • 10 Sessions
  • 30 Hours of Hands-on Training
  • Multiple Cloud Platforms for Data Integration
  • Online Practical Training
  • Learn Snowflake Skills
  • Practical Tasks, Lectures, and More
  • Data Management and Integration Content with Hands-on Training

Things You'll Learn

  • Snowflake’s unique cloud-native architecture
  • Efficient data loading and unloading techniques
  • Writing and optimizing SQL queries in Snowflake
  • Secure data sharing across organizations
  • Leveraging advanced features like Time Travel and Cloning

Course Content

Introduction to Snowflake
  • Overview of Snowflake’s cloud-native architecture and its benefits.
  • Separation of compute and storage for scalability and cost-efficiency.
  • Support for multiple cloud platforms: AWS, Azure, and Google Cloud.
  • Hybrid architecture combining shared-disk and shared-nothing paradigms.
  • Core components: cloud services layer, compute layer (virtual warehouses), and storage layer.
  • Multi-cluster shared data architecture to eliminate resource contention.
  • Practical setup: creating a Snowflake account and navigating the Snowsight UI.
  • Configuring initial roles and users for secure access.
  • No hardware/software management—fully managed data platform.
  • Support for structured and semi-structured data (e.g., JSON, Avro, Parquet).
  • Key terminology: stages, pipes, tasks, databases, and schemas.
  • Hands-on exercise: creating your first database and schema.
  • Real-world examples: Why PepsiCo and Domino’s use Snowflake for high-performance data solutions.
Data Loading and Unloading
  • Techniques for loading data into Snowflake from various sources.
  • Unloading data for external use with bulk and continuous methods.
  • Using internal and external stages as temporary storage for data files.
  • `PUT` command to upload files (e.g., CSV, JSON) to Snowflake’s internal stage.
  • `COPY INTO` command to load data into tables with file format objects.
  • Handling malformed data and defining delimiters or compression settings.
  • Snowpipe setup for continuous, automated loading from cloud storage (S3, Azure Blob, GCS).
  • Configuring auto-ingest notifications and monitoring Snowpipe performance.
  • Exporting query results to cloud storage using `COPY INTO `.
  • Options for file partitioning and encryption during unloading.
  • Hands-on lab: Loading a 1GB dataset from S3 into Snowflake.
  • Hands-on lab: Unloading aggregated data to Azure Blob Storage.
  • Preparing for enterprise-scale ETL/ELT workflows.
Snowflake SQL and Query Optimization
  • Writing efficient SQL queries tailored to Snowflake’s cloud environment.
  • Understanding Snowflake’s SQL dialect: DDL (e.g., `CREATE TABLE`) and DML (e.g., `MERGE`).
  • Querying semi-structured data using dot notation and `FLATTEN`.
  • Advanced SQL constructs: window functions, CTEs, and large-scale joins.
  • Real-world scenario: Querying sales analytics across multiple datasets.
  • Analyzing query execution plans with Snowsight’s Query Profile.
  • Identifying bottlenecks like spills to disk and optimizing performance.
  • Applying clustering keys to reduce scan times on large tables.
  • Leveraging caching: result cache and local disk cache for faster queries.
  • Adjusting virtual warehouse sizing to balance cost and speed.
  • Hands-on example: Optimizing a complex query on a 10TB dataset.
  • Achieving up to 50% reduction in query execution time.
  • Best practices for cost-effective query design in Snowflake.
Data Sharing and Security
  • Snowflake’s secure data sharing capabilities for collaboration.
  • Sharing data with other Snowflake accounts (e.g., partners, subsidiaries).
  • Using Data Share objects and Reader Accounts for non-Snowflake users.
  • Creating shares and granting privileges (e.g., `USAGE`, `SELECT`).
  • Monitoring usage with the `ACCOUNT_USAGE` schema.
  • Hands-on exercise: Sharing a sales dataset with a partner securely.
  • Role-based access control (RBAC): defining roles and hierarchies.
  • Setting up privileges for fine-grained access management.
  • End-to-end encryption for data at rest and in transit.
  • Configuring multi-factor authentication (MFA) and key pair authentication.
  • Compliance features: Support for HIPAA, GDPR, and more.
  • Hands-on lab: Securing a database with sensitive customer data.
  • Validating access controls and ensuring data protection.
Advanced Features
  • Time Travel: Querying historical data and recovering dropped objects.
  • Using `SELECT ... AT` and `UNDROP` for data recovery (up to 90 days).
  • Hands-on: Recovering a table deleted a week ago.
  • Zero-Copy Cloning: Instant duplication of databases/tables without extra cost.
  • Hands-on: Cloning a 5TB data warehouse for testing.
  • Streams: Tracking table changes for change data capture (CDC).
  • Tasks: Automating workflows like hourly aggregations.
  • Integrating Streams and Tasks with Snowpipe for real-time updates.
  • Materialized views for precomputed query results.
  • External functions with AWS Lambda for custom processing.
  • Dynamic table partitioning for optimized performance.
  • Hands-on project: Building an automated ETL pipeline.
  • Hands-on project: Reverting a production database to a prior state.

Why Choose This Course?

  • Expert-led sessions by industry professionals
  • Hands-on labs with real-world scenarios
  • Flexible online delivery to suit your schedule
  • Comprehensive case studies and practical tasks
  • Prepares you for Snowflake certification
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