Introduction
The explosion of data and the demand for insights
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What we’ll cover in this course
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1. Modern Data Engineering with Snowflake
Modern data engineering with snowflake
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You’ve probably done some data engineering in the past
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Preparing your development environment
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Build a really simple data pipeline in snowflake
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2. Batch Data Ingestion with Snowflake
What is data ingestion?
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Batch ingestion with snowflake
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Loading data from snowflake marketplace
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Loading data using snowflake’s web interface
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Optimize compute resources for efficient batch ingestion
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Loading data using snowflake CLI
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Loading data using the COPY INTO command
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Ingesting data from other data systems using connectors
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Recap and best practices for batch ingestion
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3. Data Transformations with Snowflake
What are data transformations?
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Data transformations with SQL
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Data transformations with snowpark
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Computations with user-defined functions
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Efficient transformations with streams
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Complex procedural logic with stored procedures
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Automatic transformations with dynamic tables
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Data transformations in visual studio code (optional)
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Recap and best practices for data transformations
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4. Delivering data products with Snowflake
Delivery of data products
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Data sharing on snowflake marketplace
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Streamlit in snowflake applications
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Snowflake native applications
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Recap and best practices for data product delivery
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5. Orchestrating Continuous Data Pipelines with Snowflake
What is orchestration?
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Automation with tasks
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Orchestration with DAGs
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Recap and best practices for pipeline orchestration
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Conclusion
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Ex_Files_Intro_Modern_Data_Engineering_Snowflake.zip
(1.1 MB)