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Overview
This two-day, role-specific course presents additional topics and a deep dive into select subjects for the Data Engineer through the lens of the data engineering lifecycle. The course covers Snowflake concepts, features, considerations, and best practices intended for stakeholders who will be accessing, developing, and querying datasets for analytic tasks, and building data pipelines in Snowflake. This course consists of data engineering concepts delivered through lectures, demos, labs, and discussions.
Develop applications for Snowflake, including comprehensive ANSI standard SQL support. Identify and describe various data modelling techniques and architectures deployed on the Snowflake Platform. Govern data stored and accessed in Snowflake effectively. Exploit Snowflake capabilities to work effectively with structured, semi-structured, and unstructured data in Snowflake. Use Snowflake’s SQL extensibility features, such as user-defined functions and stored procedures. Employ the Snowpark client libraries to query and transform data in a data pipeline and build applications that process data in Snowflake without moving data to the system running the application. Automate data ingestion and expand data lake capabilities using Snowflake.
Data Analysts Data Engineers Data Scientists Database Architects Database Administrators Data Application Developers
Coming Soon...
Module 1: Snowflake Overview and Architecture Recap Module 2: Data Engineering Workflow Recap Module 3: Data Storage Table Formats and Apache Iceberg™ Tables Apache Iceberg™ Tables in Snowflake Hybrid Tables in Snowflake Define and Implement Hybrid Tables Cost Analysis and Limitations Module 4: Ingestion Schema Detection Schema Evolution Visualizing Data Ingestion Module 5: Transformation Developing for Snowflake Overview User Defined Functions (Java and Python) User Defined Table Functions (Java and Python) Snowpark Stored Procedures (Java, Scala, and Python) Working With Snowpark Module 6: Data Platform Architecture Data Modeling Data Vault Introduction Module 7: Supporting Platform Features Data Governance Overview Classification and Object Tagging Object Dependencies Access History Snowflake Policies Tag-based Masking Policies External Tokenization Module 8: Performance Optimization Search Optimization Service Query Acceleration Service Module 9: Delivery Snowflake Python API Snowflake SQLAPI Streamlit in Snowflake Module 10: Orchestration Scheduling Workflows with Airflow Snowflake Python Task API Module 11: Management and Observability Observability on Snowflake No-code Pipeline Observability Within Snowsight Cost Governance Framework Logging and Tracing
Module 1: Snowflake Overview and Architecture Recap
Module 2: Data Engineering Workflow Recap
Module 3: Data Storage
Module 4: Ingestion
Module 5: Transformation
Module 6: Data Platform Architecture
Module 7: Supporting Platform Features
Module 8: Performance Optimization
Module 9: Delivery
Module 10: Orchestration
Module 11: Management and Observability
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